The Journal of Information Processing Systems
(JIPS) is the official international journal of the Korea Information Processing Society.
As information processing systems are progressing at a rapid pace, the Korea Information Processing Society is committed to providing researchers and other professionals
with the academic information and resources they need to keep abreast with ongoing developments. The JIPS aims to be a premier source that enables researchers and professionals
all over the world to promote, share, and discuss all major research issues and developments in the field of information processing systems and other related fields.
ISSN: 1976-913X (Print), ISSN: 2092-805X (Online)
[Dec. 12, 2016] Call for papers about Special sections scheduled in 2017 are registered. Please refer to here for details.
[Oct. 1, 2016] Call for papers about a new special issue titled "Smart Standards, Algorithms and Frameworks for Interoperability in Internet of Things" is now registered. Please refer to here for details.
[Aug. 20, 2016] Since August 20, 2016, the JIPS has started to manage two fast tracks as well as the regular track, and authors has been required to pay the publication charge. Please refer to the details on the author information page.
[Aug. 1, 2016] Since August 2016, the JIPS has been indexed in "Emerging Sources Citation Index (ESCI)", a new Web of Science index managed by Thomson Reuters, launched in late 2015 for journals that have passed an initial evaluation for inclusion in SCI/SCIE/AHCI/SSCI indexes. Indexing in the ESCI will improve the visibility of the JIPS and provide a mark of quality. This achievement is good for all authors of the JIPS. For more information about ESCI, please see the ESCI fact sheet file.
Journal of Information Processing Systems, Vol. 13, No.3, 2017
The Journal of Information Processing Systems (JIPS) publishes a broad array of subjects related to information communication technology across prevalent and advanced fields including system, network, architecture, algorithm, application, security, and so forth. As the official international journal published by the Korean Information Processing Society and a prominent, multidisciplinary journal throughout the world, JIPS is being indexed in ESCI, SCOPUS, EI COMPENDEX, DOI, DBLP, EBSCO, Google Scholar, and CrossRef. The purpose of JIPS is to provide a prominent, influential forum wherein researchers and professionals gather to promote, share, and discuss all major research issues and developments. Published theoretical and practical articles have contributed to related research areas by presenting new techniques, concepts, or analyses, featuring experience reports, experiments involving the implementation and application of new theories, and tutorials on state-of-the-art technologies related to information processing systems. The subjects covered by this journal include, but are not limited to, topics related to computer systems and theories, multimedia systems and graphics, communication systems and security, and software systems and applications
Associative and bidirectional associative memories are examples of associative structures studied intensively in the literature. The underlying idea is to realize associative mapping so that the recall processes (one- directional and bidirectional ones) are realized with minimal recall errors. Associative and fuzzy associative memories have been studied in numerous areas yielding efficient applications for image recall and enhancements and fuzzy controllers, which can be regarded as one-directional associative memories. In this study, we revisit and augment the concept of associative memories by offering some new design insights where the corresponding mappings are realized on the basis of a related collection of landmarks (prototypes) over which an associative mapping becomes spanned. In light of the bidirectional character of mappings, we have developed an augmentation of the existing fuzzy clustering (fuzzy c-means, FCM) in the form of a so- called collaborative fuzzy clustering. Here, an interaction in the formation of prototypes is optimized so that the bidirectional recall errors can be minimized. Furthermore, we generalized the mapping into its granular version in which numeric prototypes that are formed through the clustering process are made granular so that the quality of the recall can be quantified. We propose several scenarios in which the allocation of information granularity is aimed at the optimization of the characteristics of recalled results (information granules) that are quantified in terms of coverage and specificity. We also introduce various architectural augmentations of the associative structures.
Multimedia is a ubiquitous and indispensable part of our daily life and learning such as audio, image, and video. Objective and subjective quality evaluations play an important role in various multimedia applications. Blind image quality assessment (BIQA) is used to indicate the perceptual quality of a distorted image, while its reference image is not considered and used. Blur is one of the common image distortions. In this paper, we propose a novel BIQA index for Gaussian blur distortion based on the fact that images with different blur degree will have different changes through the same blur. We describe this discrimination from three aspects: color, edge, and structure. For color, we adopt color histogram; for edge, we use edge intensity map, and saliency map is used as the weighting function to be consistent with human visual system (HVS); for structure, we use structure tensor and structural similarity (SSIM) index. Numerous experiments based on four benchmark databases show that our proposed index is highly consistent with the subjective quality assessment.
In this paper, we present a new texture image retrieval method which combines color and texture features extracted from images by a set of multi-resolution multi-direction (MRMD) filters. The MRMD filter set chosen is simple and can be separable to low and high frequency information, and provides efficient multi- resolution and multi-direction analysis. The color space used is HSV color space separable to hue, saturation, and value components, which are easily analyzed as showing characteristics similar to the human visual system. This experiment is conducted by comparing precision vs. recall of retrieval and feature vector dimensions. Images for experiments include Corel DB and VisTex DB; Corel_MR DB and VisTex_MR DB, which are transformed from the aforementioned two DBs to have multi-resolution images; and Corel_MD DB and VisTex_MD DB, transformed from the two DBs to have multi-direction images. According to the experimental results, the proposed method improves upon the existing methods in aspects of precision and recall of retrieval, and also reduces feature vector dimensions.
In the centralized cloud controlled environment, the decision-making and monitoring play crucial role where in the host controller (HC) manages the resources across hosts in data center (DC). HC does virtual machine (VM) and physical hosts management. The VM management includes VM creation, monitoring, and migration. If HC down,the services hosted by various hosts in DC can’t be accessed outside the DC. Decentralized VM management avoids centralized failure by considering one of the hosts from DC as HC that helps in maintaining DC in running state. Each host in DC has many VM’s with the threshold limit beyond which it can’t provide service.To maintain threshold , the host’s in DC does VM migration across various hosts. The data in migration is in the form of plaintext, the intruder can analyze packet movement and can control hosts traffic. The incorporation of security mechanism on hosts in DC helps protecting data in migration. This paper discusses an approach for dynamic HC selection, VM selection and secure VM migration over cloud environment.
In this study, we proposed a new approach to segment ground and nonground points gained from a 3D laser range sensor. The primary aim of this research was to provide a fast and effective method for ground segmentation. In each frame, we divide the point cloud into small groups. All threshold points and start- ground points in each group are then analyzed. To determine threshold points we depend on three features: gradient, lost threshold points, and abnormalities in the distance between the sensor and a particular threshold point. After a threshold point is determined, a start-ground point is then identified by considering the height difference between two consecutive points. All points from a start-ground point to the next threshold point are ground points. Other points are nonground. This process is then repeated until all points are labelled
In this paper, an improved zone-based routing protocol for heterogeneous wireless sensor networks is proposed. The proposed protocol has fixed the sized zone according to the distance from the base station and used a dynamic clustering technique for advanced nodes to select a cluster head with maximum residual energy to transmit the data. In addition, we select an optimal route with minimum energy consumption for normal nodes and conserve energy by state transition throughout data transmission. Simulation results indicated that the proposed protocol performed better than the other algorithm by reducing energy consumption and providing a longer network lifetime and better throughput of data packets
Due to the rapid growth of the amount of data, research on bigdata processing has been highlighted. For bigdata processing, CUBRID Shard is able to support query processing in parallel way by dividing the database into a number of CUBRID servers. However, CUBRID Shard can answer a user’s query only when the query is required to gain accesses to a single CUBRID server, instead of multiple ones. To solve the problem, in this paper we propose a CUBRID based distributed parallel query processing system that can answer a user’s query in parallel and distributed manner. Finally, through the performance evaluation, we show that our proposed system provides 2–3 times better performance on query processing time than the existing CUBRID Shard
Massive volumes of GPS trajectory data bring challenges to storage and processing. These issues can be addressed by compression algorithm which can reduce the size of the trajectory data. A key requirement for GPS trajectory compression algorithm is to reduce the size of the trajectory data while minimizing the loss of information. Synchronized Euclidean distance (SED) as an important error measure is adopted by most of the existing algorithms. In order to further reduce the SED error, an improved algorithm for open window time ratio (OPW-TR) called local optimum open window time ratio (LO-OPW-TR) is proposed. In order to make SED error smaller, the anchor points are selected by calculating point’s accumulated synchronized Euclidean distance (ASED). A variety of error metrics are used for the algorithm evaluation. The experimental results show that the errors of our algorithm are smaller than the existing algorithms in terms of SED and speed errors under the same compression ratio
The amount of multimedia traffic over the Internet has been increasing because of the development of networks and mobile devices. Accordingly, studies on multicast, which is used to provide efficient multimedia and video services, have been conducted. In particular, studies on centralized multicast tree construction have attracted attention with the advent of software-defined networking. Among the centralized multicast tree construction algorithms, the group Takahashi and Matsuyama (GTM) algorithm is the most commonly used in multiple multicast tree construction. However, the GTM algorithm considers only the network-cost overhead when constructing multicast trees; it does not consider the temporary service disruption that arises from a link change for users receiving an existing service. Therefore, in this study, we propose a multiple multicast tree construction algorithm that can reduce network cost while avoiding considerable degradation of service quality to users. This is accomplished by considering both network-cost and link-change overhead of users. Experimental results reveal that, compared to the GTM algorithm, the proposed algorithm significantly improves the user-experienced quality of service by substantially reducing the number of link- changed users while only slightly adding to the network-cost overhead.
Cyberbullying has been an emerging issue in recent years where research has revealed that users generally spend an increasing amount of time in social networks and forums to keep connected with each other. However, issue arises when cyberbullies are able to reach their victims through these social media platforms. There are different types of cyberbullying and like traditional bullying; it causes victims to feel overly self- conscious, increases their tendency to self-harm and generally affects their mental state negatively. Such situations occur due to security issues such as user anonymity and the lack of content restrictions in some social networks or web forums. In this paper, we highlight the existing solutions, which are Intrusion Prevention System and Intrusion Detection System from a number of researchers. However, even with such solutions, cyberbullying acts still occurs at an alarming rate. As such, we proposed an alternative solution that aims to prevent cyberbullying activities at a younger age, e.g., young children. The application would provide an alternative method to preventing cyberbullying activities among the younger generations in the future
Cloud computing is an attractive solution that can provide low cost storage and powerful processing capabilities for government agencies or enterprises of small and medium size. Yet the confidentiality of information should be considered by any organization migrating to cloud, which makes the research on relational database system based on encryption schemes to preserve the integrity and confidentiality of data in cloud be an interesting subject. So far there have been various solutions for realizing SQL queries on encrypted data in cloud without decryption in advance, where generally homomorphic encryption algorithm is applied to support queries with aggregate functions or numerical computation. But the existing homomorphic encryption algorithms cannot encrypt floating-point numbers. So in this paper, we present a mechanism to enable the trusted party to encrypt the floating-points by homomorphic encryption algorithm and partial trusty server to perform summation on their ciphertexts without revealing the data itself. In the first step, we encode floating-point numbers to hide the decimal points and the positive or negative signs. Then, the codes of floating-point numbers are encrypted by homomorphic encryption algorithm and stored as sequences in cloud. Finally, we use the data structure of DoubleListTree to implement the aggregate function of SUM and later do some extra processes to accomplish the summation
Recently, there has been an increase in the number of hazardous events, such as fire accidents. Monitoring systems that rely on human resources depend on people; hence, the performance of the system can be degraded when human operators are fatigued or tensed. It is easy to use fire alarm boxes; however, these are frequently activated by external factors such as temperature and humidity. We propose an approach to fire detection using an image processing technique. In this paper, we propose a fire detection method using multi- channel information and gray level co-occurrence matrix (GLCM) image features. Multi-channels consist of RGB, YCbCr, and HSV color spaces. The flame color and smoke texture information are used to detect the flames and smoke, respectively. The experimental results show that the proposed method performs better than the previous method in terms of accuracy of fire detection
Due to the rapid growth and expansion of the Internet, the digital multimedia such as image, audio and video are available for everyone. Anyone can make unauthorized copying for any digital product. Accordingly, the owner of these products cannot protect his ownership. Unfortunately, this situation will restrict any improvement which can be done on the digital media production in the future. Some procedures have been proposed to protect these products such as cryptography and watermarking techniques. Watermarking means embedding a message such as text, the image is called watermark, yet, in a host such as a text, an image, an audio, or a video, it is called a cover. Watermarking can provide and ensure security, data authentication and copyright protection for the digital media. In this paper, a new watermarking method of still image is proposed for the purpose of copyright protection. The procedure of embedding watermark is done in a transform domain. The discrete cosine transform (DCT) is exploited in the proposed method, where the watermark is embedded in the selected coefficients according to several criteria. With this procedure, the deterioration on the image is minimized to achieve high invisibility. Unlike the traditional techniques, in this paper, a new method is suggested for selecting the best blocks of DCT coefficients. After selecting the best DCT coefficients blocks, the best coefficients in the selected blocks are selected as a host in which the watermark bit is embedded. The coefficients selection is done depending on a weighting function method, where this function exploits the values and locations of the selected coefficients for choosing them. The experimental results proved that the proposed method has produced good imperceptibility and robustness for different types of attacks
Mobile nodes can't always connect each other in DTNs (delay tolerant networks). Many DTN routing protocols that favor the “multi-hop forwarding” are proposed to solve these network problems. But they also lead to intolerant delivery cost so that designing a overhead-efficient routing protocol which is able to perform well in delivery ratio with lower delivery cost at the same time is valuable. Therefore, we utilize the small-world property and propose a new delivery metric called multi-probability to design our relay node selection principles that nodes with lower delivery predictability can also be selected to be the relay nodes if one of their history nodes has higher delivery predictability. So, we can find more potential relay nodes to reduce the forwarding overhead of successfully delivered messages through our proposed algorithm called HESnW. We also apply our new messages copies allocation scheme to optimize the routing performance. Comparing to existing routing algorithms, simulation results show that HESnW can reduce the delivery cost while it can also obtain a rather high delivery ratio.
In this paper, we propose the opportunistic non-orthogonal multiple access (NOMA)-based cooperative relaying system (CRS) with channel state information (CSI) available at the source, where CSI for the source- to-destination and source-to-relay links is used for opportunistic transmission. Using the CSI, for opportunistic transmission, the source instantaneously chooses between the direct transmission and the cooperative NOMA transmission. We provide an asymptotic expression for the average achievable rate of the opportunistic NOMA-based CRS under Rayleigh fading channels. We verify the asymptotic analysis through Monte Carlo simulations, and compare the average achievable rates of the opportunistic NOMA-based CRS and the conventional one for various channel powers and power allocation coefficients used for NOMA
The recent advent of increasingly affordable and powerful 3D scanning devices capable of capturing high resolution range data about real-world objects and environments has fueled research into effective 3D surface reconstruction techniques for rendering the raw point cloud data produced by many of these devices into a form that would make it usable in a variety of application domains. This paper, therefore, provides an overview of the existing literature on surface reconstruction from 3D point clouds. It explains some of the basic surface reconstruction concepts, describes the various factors used to evaluate surface reconstruction methods, highlights some commonly encountered issues in dealing with the raw 3D point cloud data and delineates the tradeoffs between data resolution/accuracy and processing speed. It also categorizes the various techniques for this task and briefly analyzes their empirical evaluation results demarcating their advantages and disadvantages. The paper concludes with a cross-comparison of methods which have been evaluated on the same benchmark data sets along with a discussion of the overall trends reported in the literature. The objective is to provide an overview of the state of the art on surface reconstruction from point cloud data in order to facilitate and inspire further research in this area.
Gene identification is at the center of genomic studies. Although the first phase of the Encyclopedia of DNA Elements (ENCODE) project has been claimed to be complete, the annotation of the functional elements is far from being so. Computational methods in gene identification continue to play important roles in this area and other relevant issues. So far, a lot of work has been performed on this area, and a plethora of computational methods and avenues have been developed. Many review papers have summarized these methods and other related work. However, most of them focus on the methodologies from a particular aspect or perspective. Different from these existing bodies of research, this paper aims to comprehensively summarize the mainstream computational methods in gene identification and tries to provide a short but concise technical reference for future studies. Moreover, this review sheds light on the emerging trends and cutting-edge techniques that are believed to be capable of leading the research on this field in the future.
In this paper we present some research results on computing intensive applications using modern high performance architectures and from the perspective of high computational needs. Computing intensive applications are an important family of applications in distributed computing domain. They have been object of study using different distributed computing paradigms and infrastructures. Such applications distinguish for their demanding needs for CPU computing, independently of the amount of data associated with the problem instance. Among computing intensive applications, there are applications based on simulations, aiming to maximize system resources for processing large computations for simulation. In this research work, we consider an application that simulates scheduling and resource allocation in a Grid computing system using Genetic Algorithms. In such application, a rather large number of simulations is needed to extract meaningful statistical results about the behavior of the simulation results. We study the performance of Oracle Grid Engine for such application running in a Cluster of high computing capacities. Several scenarios were generated to measure the response time and queuing time under different workloads and number of nodes in the cluster.
The accuracy of training-based activity recognition depends on the training procedure and the extent to which the training dataset comprehensively represents the activity and its varieties. Additionally, training incurs substantial cost and effort in the process of collecting training data. To address these limitations, we have developed a training-free activity recognition approach based on a fuzzy logic algorithm that utilizes a generic activity model and an associated activity semantic knowledge. The approach is validated through experimentation with real activity datasets. Results show that the fuzzy logic based algorithms exhibit comparable or better accuracy than other trainingbased approaches.
Recent technological advances provide the opportunity to use large amounts of multimedia data from a multitude of sensors with different modalities (e.g., video, text) for the detection and characterization of criminal activity. Their integration can compensate for sensor and modality deficiencies by using data from other available sensors and modalities. However, building such an integrated system at the scale of neighborhood and cities is challenging due to the large amount of data to be considered and the need to ensure a short response time to potential criminal activity. In this paper, we present a system that enables multi-modal data collection at scale and automates the detection of events of interest for the surveillance and reconnaissance of criminal activity. The proposed system showcases novel analytical tools that fuse multimedia data streams to automatically detect and identify specific criminal events and activities. More specifically, the system detects and analyzes series of incidents (an incident is an occurrence or artifact relevant to a criminal activity extracted from a single media stream) in the spatiotemporal domain to extract events (actual instances of criminal events) while cross-referencing multimodal media streams and incidents in time and space to provide a comprehensive view to a human operator while avoiding information overload. We present several case studies that demonstrate how the proposed system can provide law enforcement personnel with forensic and real time tools to identify and track potential criminal activity.
The confinement problem was first noted four decades ago. Since then, a huge amount of efforts have been spent on defining and mitigating the problem. The evolution of technologies from traditional operating systems to mobile and cloud computing brings about new security challenges. It is perhaps timely that we review the work that has been done. We discuss the foundational principles from classical works, as well as the efforts towards solving the confinement problem in three domains: operating systems, mobile computing, and cloud computing. While common issues exist across all three domains, unique challenges arise for each of them, which we discuss.
Since a social network by definition is so diverse, the problem of estimating the preferences of its users is becoming increasingly essential for personalized applications, which range from service recommender systems to the targeted advertising of services. However, unlike traditional estimation problems where the underlying target distribution is stationary; estimating a user"'"s interests typically involves non-stationary distributions. The consequent time varying nature of the distribution to be tracked imposes stringent constraints on the "unlearning” capabilities of the estimator used. Therefore, resorting to strong estimators that converge with a probability of 1 is inefficient since they rely on the assumption that the distribution of the user"'"s preferences is stationary. In this vein, we propose to use a family of stochastic-learning based Weak estimators for learning and tracking a user"'"s time varying interests. Experimental results demonstrate that our proposed paradigm outperforms some of the traditional legacy approaches that represent the state-of-the-art technology.
The most important criterion for achieving the maximum performance in a wireless mesh network (WMN) is to limit the interference within the network. For this purpose, especially in a multi-radio network, the best option is to use non-overlapping channels among different radios within the same interference range. Previous works that have considered non-overlapping channels in IEEE 802.11a as the basis for performance optimization, have considered the link quality across all channels to be uniform. In this paper, we present a measurement-based study of link quality across all channels in an IEEE 802.11a-based indoor WMN test bed. Our results show that the generalized assumption of uniform performance across all channels does not hold good in practice for an indoor environment and signal quality depends on the geometry around the me routers.
This paper describes different aspects of a typical RFID implementation. Section 1 provides a brief overview of the concept of Automatic Identification and compares the use of different technologies while Section 2 describes the basic components of a typical RFID system. Section 3 and Section 4 deal with the detailed specifications of RFID transponders and RFID interrogators respectively. Section 5 highlights different RFID standards and protocols and Section 6 enumerates the wide variety of applications where RFID systems are known to have made a positive improvement. Section 7 deals with privacy issues concerning the use of RFIDs and Section 8 describes common RFID system vulnerabilities. Section 9 covers a variety of RFID security issues, followed by a detailed listing of countermeasures and precautions in Section 10.
Granular Computing has emerged as a unified and coherent framework of designing, processing, and interpretation of information granules. Information granules are formalized within various frameworks such as sets (interval mathematics), fuzzy sets, rough sets, shadowed sets, probabilities (probability density functions), to name several the most visible approaches. In spite of the apparent diversity of the existing formalisms, there are some underlying commonalities articulated in terms of the fundamentals, algorithmic developments and ensuing application domains. In this study, we introduce two pivotal concepts: a principle of justifiable granularity and a method of an optimal information allocation where information granularity is regarded as an important design asset. We show that these two concepts are relevant to various formal setups of information granularity and offer constructs supporting the design of information granules and their processing. A suite of applied studies is focused on knowledge management in which case we identify several key categories of schemes present there.
In earlier days, most of the data carried on communication networks was textual data requiring limited bandwidth. With the rise of multimedia and network technologies, the bandwidth requirements of data have increased considerably. If a network link at any time is not able to meet the minimum bandwidth requirement of data, data transmission at that path becomes difficult, which leads to network congestion. This causes delay in data transmission and might also lead to packet drops in the network. The retransmission of these lost packets would aggravate the situation and jam the network. In this paper, we aim at providing a solution to the problem of network congestion in mobile ad hoc networks [1, 2] by designing a protocol that performs routing intelligently and minimizes the delay in data transmission. Our Objective is to move the traffic away from the shortest path obtained by a suitable shortest path calculation algorithm to a less congested path so as to minimize the number of packet drops during data transmission and to avoid unnecessary delay. For this we have proposed a protocol named as Congestion Aware Selection Of Path With Efficient Routing (CASPER). Here, a router runs the shortest path algorithm after pruning those links that violate a given set of constraints. The proposed protocol has been compared with two link state protocols namely, OSPF [3, 4] and OLSR [5, 6, 7, 8].The results achieved show that our protocol performs better in terms of network throughput and transmission delay in case of bulky data transmission.
Vehicular networks are a promising application of mobile ad hoc networks. In this paper, we introduce an efficient broadcast technique, called CB-S (Cell Broadcast for Streets), for vehicular networks with occlusions such as skyscrapers. In this environment, the road network is fragmented into cells such that nodes in a cell can communicate with any node within a two cell distance. Each mobile node is equipped with a GPS (Global Positioning System) unit and a map of the cells. The cell map has information about the cells including their identifier and the coordinates of the upper-right and lower-left corner of each cell. CB-S has the following desirable property. Broadcast of a message is performed by rebroadcasting the message from every other cell in the terrain. This characteristic allows CB-S to achieve an efficient performance. Our simulation results indicate that messages always reach all nodes in the wireless network. This perfect coverage is achieved with minimal overhead. That is, CB-S uses a low number of nodes to disseminate the data packets as quickly as probabilistically possible. This efficiency gives it the advantage of low delay. To show these benefits, we give simulations results to compare CB-S with four other broadcast techniques. In practice, CB-S can be used for information dissemination, or to reduce the high cost of destination discovery in routing protocols. By also specify the radius of affected zone, CB-S is also more efficient when broadcast to a subset of the nodes is desirable.
Cryptographic hash functions reduce inputs of arbitrary or very large length to a short string of fixed length. All hash function designs start from a compression function with fixed length inputs. The compression function itself is designed from scratch, or derived from a block cipher or a permutation. The most common procedure to extend the domain of a compression function in order to obtain a hash function is a simple linear iteration; however, some variants use multiple iterations or a tree structure that allows for parallelism. This paper presents a survey of 17 extenders in the literature. It considers the natural question whether these preserve the security properties of the compression function, and more in particular collision resistance, second preimage resistance, preimage resistance and the pseudo-random oracle property.
This paper proposes a novel reversible data hiding scheme based on a Vector Quantization (VQ) codebook. The proposed scheme uses the principle component analysis (PCA) algorithm to sort the codebook and to find two similar codewords of an image block. According to the secret to be embedded and the difference between those two similar codewords, the original image block is transformed into a difference number table. Finally, this table is compressed by entropy coding and sent to the receiver. The experimental results demonstrate that the proposed scheme can achieve greater hiding capacity, about five bits per index, with an acceptable bit rate. At the receiver end, after the compressed code has been decoded, the image can be recovered to a VQ compressed image.
The interconnection of mobile devices in urban environments can open up a lot of vistas for collaboration and content-based services. This will require setting up of a network in an urban environment which not only provides the necessary services to the user but also ensures that the network is secure and energy efficient. In this paper, we propose a secure, energy efficient dynamic routing protocol for heterogeneous wireless sensor networks in urban environments. A decision is made by every node based on various parameters like longevity, distance, battery power which measure the node and link quality to decide the next hop in the route. This ensures that the total load is distributed evenly while conserving the energy of battery-constrained nodes. The protocol also maintains a trusted population for each node through Dynamic Trust Factor (DTF) which ensures secure communication in the environment by gradually isolating the malicious nodes. The results obtained show that the proposed protocol when compared with another energy efficient protocol (MMBCR) and a widely accepted protocol (DSR) gives far better results in terms of energy efficiency. Similarly, it also outdoes a secure protocol (QDV) when it comes to detecting malicious nodes in the network.
The trend of Next Generation Networks’ (NGN) evolution is towards providing multiple and multimedia services to users through ubiquitous networks. The aim of IP Multimedia Subsystem (IMS) is to integrate mobile communication networks and computer networks. The IMS plays an important role in NGN services, which can be achieved by heterogeneous networks and different access technologies. IMS can be used to manage all service related issues such as Quality of Service (QoS), Charging, Access Control, User and Services Management. Nowadays, internet technology is changing with each passing day. New technologies yield new impact to IMS. In this paper, we perform a survey of IMS and discuss the different impacts of new technologies on IMS such as P2P, SCIM, Web Service and its security issues.
Due to the convergence of voice, data, and video, today’s telecom operators are facing the complexity of service and network management to offer differentiated value-added services that meet customer expectations. Without the operations support of well-developed Business Support System/Operations Support System (BSS/OSS), it is difficult to timely and effectively provide competitive services upon customer request. In this paper, a suite of NGOSS-based Telecom OSS (TOSS) is developed for the support of fulfillment and assurance operations of telecom services and IT services. Four OSS groups, TOSS-P (intelligent service provisioning), TOSS-N (integrated large-scale network management), TOSS-T (trouble handling and resolution), and TOSS-Q (end-to-end service quality management), are organized and integrated following the standard telecom operation processes (i.e., eTOM). We use IPTV and IP-VPN operation scenarios to show how these OSS groups co-work to support daily business operations with the benefits of cost reduction and revenue acceleration.
By providing ubiquitous Internet connectivity, wireless networks offer more convenient ways for users to surf the Internet. However, wireless networks encounter more technological challenges than wired networks, such as bandwidth, security problems, and handoff latency. Thus, this paper proposes new technologies to solve these problems. First, a Security Access Gateway (SAG) is proposed to solve the security issue. Originally, mobile terminals were unable to process high security calculations because of their low calculating power. SAG not only offers high calculating power to encrypt the encryption demand of SAG¡¯s domain, but also helps mobile terminals to establish a multiple safety tunnel to maintain a secure domain. Second, Robust Header Compression (RoHC) technology is adopted to increase the utilization of bandwidth. Instead of Access Point (AP), Access Gateway (AG) is used to deal with the packet header compression and de-compression from the wireless end. AG¡¯s high calculating power is able to reduce the load on AP. In the original architecture, AP has to deal with a large number of demands by header compression/de-compression from mobile terminals. Eventually, wireless networks must offer users ¡°Mobility¡± and ¡°Roaming¡±. For wireless networks to achieve ¡°Mobility¡± and ¡°Roaming,¡± we can use Mobile IPv6 (MIPv6) technology. Nevertheless, such technology might cause latency. Furthermore, how the security tunnel and header compression established before the handoff can be used by mobile terminals handoff will be another great challenge. Thus, this paper proposes to solve the problem by using Early Binding Updates (EBU) and Security Access Gateway (SAG) to offer a complete mechanism with low latency, low handoff mechanism calculation, and high security.
Face recognition presents a challenging problem in the field of image analysis and computer vision, and as such has received a great deal of attention over the last few years because of its many applications in various domains. Face recognition techniques can be broadly divided into three categories based on the face data acquisition methodology: methods that operate on intensity images; those that deal with video sequences; and those that require other sensory data such as 3D information or infra-red imagery. In this paper, an overview of some of the well-known methods in each of these categories is provided and some of the benefits and drawbacks of the schemes mentioned therein are examined. Furthermore, a discussion outlining the incentive for using face recognition, the applications of this technology, and some of the difficulties plaguing current systems with regard to this task has also been provided. This paper also mentions some of the most recent algorithms developed for this purpose and attempts to give an idea of the state of the art of face recognition technology.
With regard to ethical standards, the JIPS takes plagiarism very seriously and thoroughly checks all articles.
The JIPS defines research ethics as securing objectivity and accuracy in the execution of research and the conclusion of results without any unintentional errors resulting from negligence or incorrect knowledge, etc.
and without any intentional misconduct such as falsification, plagiarism, etc. When an author submits a paper to the JIPS online submission and peer-review system,
he/she should also upload the separate file "author check list" which contains a statement that all his/her research has been performed in accordance with ethical standards.
Among the JIPS editorial board members, there are four associate manuscript editors who support the JIPS by dealing with any ethical problems associated with the publication process
and give advice on how to handle cases of suspected research and publication misconduct. When the JIPS managing editor looks over submitted papers and checks that they are suitable for further processing,
the managing editor also routes them to the CrossCheck service provided by iTenticate. Based on the results provided by the CrossCheck service, the JIPS associate manuscript editors inform the JIPS editor-in-chief of any plagiarism that is detected in a paper.
Then, the JIPS editor-in-chief communicates such detection to the author(s) while rejecting the paper.
Since 2005, all papers published in the JIPS are subjected to a peer review and upon acceptance are immediately made
permanently available free of charge for everyone worldwide to read and download from the journal’s homepage (http://www.jips-k.org)
without any subscription fee or personal registration. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The KIPS waives paper processing charges for submissions from international authors as well as society members. This waiver policy supports and encourages the publication of quality papers, making the journal an international forum for the exchange of different ideas and experiences.