In content services where people purchase and download large-volume contents, minimizing network traffic is crucial for the service provider and the network operator since they want to lower the cost charged for bandwidth and the cost for network infrastructure, respectively. Traffic localization is an effective way of reducing network traffic. Network traffic is localized when a client can obtain the requested content files from other a near-by altruistic client instead of the source servers. The concept of the peer-assisted content distribution network (CDN) can reduce the overall traffic with this mechanism and enable service providers to minimize traffic without deploying or borrowing distributed storage. To localize traffic effectively, content files that are likely to be requested by many clients should be cached locally. This paper presents a novel traffic engineering scheme for peer-assisted CDN models. Its key idea is to control the behavior of clients by using content-oriented incentive mechanism. This approach enables us to optimize traffic flows by letting altruistic clients download content files that are most likely contributed to localizing traffic among clients. In order to let altruistic clients request the desired files, we combine content files while keeping the price equal to the one for a single content. This paper presents a solution for optimizing the selection of content files to be combined so that cross traffic in a network is minimized. We also give a model for analyzing the upper-bound performance and the numerical results.

In this letter, we argue that user resources will be still useful in the information-centric network (ICN). From this point of view, we first examine how P2P utilizing user resources looks like in ICN. Then, we identify challenging research issues to utilize user resources in ICN.

Secret sharing schemes have been proposed to protect content by dividing it into many pieces securely and distributing them over different locations. Secret sharing schemes can also be used for the secure delivery of content. The original content cannot be reconstructed by the attacker if the attacker cannot eavesdrop on all the pieces delivered from multiple content servers. This paper aims to obtain secure delivery routes for the pieces, which minimizes the probability that all the pieces can be stolen on the links composing the delivery routes. Although such a route optimization problem can be formulated using an ILP (Integer Linear Programming) model, optimum route computation based on the ILP model requires large amounts of computational resources. Thus, this paper proposes a lightweight route computation method for obtaining suboptimum delivery routes that achieve a sufficiently small probability of all the pieces being stolen. The proposed method computes the delivery routes successively by using the conventional shortest route algorithm repeatedly. The distance of the links accommodating the routes that have already been calculated is adjusted iteratively and utilized for calculation of the new shortest route. The results of a performance evaluation clarify that sufficiently optimum routes can be computed instantly even in practical large-scale networks by the proposed method, which adjusts the link distance strictly based on the risk level at the considered link.

A new information detection method has been proposed for a very fast and efficient search engine. This method is implemented on hardware system using FPGA. We take advantages of Content Addressable Memory (CAM) which has an ability of matching mode for designing the system. The CAM blocks have been designed using available memory blocks of the FPGA device to save access times of the whole system. The entire memory can return multi-match results concurrently. The system operates based on the CAMs for pattern matching, in a parallel manner, to output multiple addresses of multi-match results. Based on the parallel multi-match operations, the system can be applied for pattern matching with various required constraint conditions without using any search principles. The very fast multi-match results are achieved at 60 ns with the operation frequency 50 MHz. This increases the search performance of the information detection system which uses this method as the core system.

The applications of dynamic content updates for a group of users, for example weather reports and news broadcast, have been shown to benefit significantly from Delay Tolerant Networks (DTNs) communication mechanisms. In this paper, we study the performance of dynamic content updates over DTNs by focusing on the latest content distribution, which is an important factor of the system energy consumption and content update efficiency. By characterizing the content generating process and content sharing process, we obtain an explicit expression for the latest content distribution, and prove it theoretically. Moreover, through simulations based on two synthetical mobility models and a real-world scenario, we demonstrate the accuracy and correctness of the theoretically obtained result.

Ternary content addressable memory (TCAM) is becoming very popular for designing high-throughput forwarding engines on routers. However, TCAM has potential problems in terms of hardware and power costs, which limits its ability to deploy large amounts of capacity in IP routers. In this paper, we propose new hardware architecture for fast forwarding engines, called fast prefix search RAM-based hardware (FPS-RAM). We designed FPS-RAM hardware with the intent of maintaining the same search performance and physical user interface as TCAM because our objective is to replace the TCAM in the market. Our RAM-based hardware architecture is completely different from that of TCAM and has dramatically reduced the costs and power consumption to 62% and 52%, respectively. We implemented FPS-RAM on an FPGA to examine its lookup operation.

Despite its great success, BitTorrent suffers from the content unavailability problem where peers cannot complete their content downloads due to some missing chunks, which is caused by a shortage of seeders who hold the content in its entirety. The multi-swarm collaboration approach is a natural choice for improving content availability, since content unavailability cannot be overcome by one swarm easily. Most existing multi-swarm collaboration approaches, however, suffer from content-related limitations, which limit their application scopes. In this paper, we introduce a new kind of multi-swarm collaboration utilizing a swarm as temporal storage. In a nutshell, the collaborating swarms cache some chunks of each other that are likely to be unavailable before the content unavailability happens and share the cached chunks when the content unavailability happens. Our approach enables any swarms to collaborate with each other without the content-related limitations. Simulation results show that our approach increases the number of download completions by over 50% (26%) compared to normal BitTorrent (existing bundling approach) with low overhead. In addition, our approach shows around 30% improved download completion time compared to the existing bundling approach. The results also show that our approach enables the peers participating in our approach to enjoy better performance than other peers, which can be a peer incentive.

This paper proposes optical node architectures for the single-layer optical cross-connect (OXC) and hierarchical OXC (HOXC) that utilize dedicated add/drop switches for originating/terminating traffic at a node. For both single-layer OXC and HOXC, three architectures with different restrictions on add/drop capabilities are presented. The performance of the proposed architectures is compared through numerical experiments. The architectures significantly reduce total switch scale and minimize necessary switch size while attaining colorless, directionless and contentionless capabilities.

A hybrid buffer structured optical packet switch and its scheduling algorithm are presented for a limited number of tunable wavelength convertors (TWCs) and internal wavelengths. The hybrid buffer consists of the fiber delay line (FDL) buffer and the electronic buffer. With the proposed algorithm, it could lead realizable packet loss reduction that the LAUC-VF algorithm with only the FDL buffer does not reach. Also, we optimized the number of TWCs and internal wavelengths of the hybrid buffer structured OPS. For the fully shared TWC structure, the optimum number of TWCs and internal wavelengths to guarantee minimum packet loss is evaluated to prevent resource waste under the hybrid buffer.

In this paper a novel and effective two phase admission control (TPAC) for QoS mobile ad hoc networks is proposed that satisfies the real-time traffic requirements in mobile ad hoc networks. With a limited amount of extra overhead, TPAC can avoid network congestions by a simple and precise admission control which blocks most of the overloading flow-requests in the route discovery process. When compared with previous QoS routing schemes such as QoS-aware routing protocol and CACP protocols, it is shown from system simulations that the proposed scheme can increase the system throughput and reduce both the dropping rate and the end-to-end delay. Therefore, TPAC is surely an effective QoS-guarantee protocol to provide for real-time traffic.

In this paper, we suggest a new technology called Content Anycasting, and we show our design and evaluation of it. Content Anycasting shows how to utilize the capabilities of one of the candidate future Internet technologies that is the Flow-based network as in OpenFlow to giving new opportunities to the future internet that are currently not available. Content Anycasting aims to provide more flexible and dynamic redirection of contents. This would be very useful in extending the content server's capacity by enabling it to serve more clients, and in improving the response of the P2P networks by reducing the time of joining P2P networks. This method relies on three important ideas which are; the content based networking, decision making by the network in a similar manner to anycast, and the participation of user clients in providing the service. This is done through the use of the flow-based actions in flow-based network and having some modifications to the content server and client.

Coscheduling has been gained a resurgence of interest as an effective technique to enhance the performance of parallel applications in multi-programmed clusters. However, existing coscheduling schemes do not adequately handle priority boost conflicts, leading to significantly degraded performance. To address this problem, in our previous study, we devised a novel algorithm that reorders the scheduling sequence of conflicting processes based on the rescheduling latency of their correspondents in remote nodes. In this paper, we exhaustively explore the design issues and implementation details of our contention-aware coscheduling scheme over Myrinet-based cluster system. We also practically analyze the impact of various system parameters and job characteristics on the performance of all considered schemes on a heterogeneous Linux cluster using a generic coscheduling framework. The results show that our approach outperforms existing schemes (by up to 36.6% in avg. job response time), reducing both boost conflict ratio and overall message delay.

In this paper, we are concerned about content-based networking (CBN) at extreme scales, characterized by a large number of widely spread consumers, heterogeneous consumer requirements, huge volume of publications, and the scarcity of end-to-end bandwidth. We extend CBN with a generic service model that allows consumers to express their interests in future publications including cached content, but also to quantify the maximum amount of information they are willing to consume. We take advantage of this knowledge to pace the dissemination process and therefore, enhance the service efficiency. Early evaluation results show gains of up to 80% compared to a baseline CBN model.

Rapid developments in mobile technology have transformed mobile phones into mobile multimedia devices. Due to these advancements, user created mobile content is on the increase, both in terms of quality and quantity. To keep pace with such movements, the new networking technology named content centric networking (CCN), which is optimized for content sharing, has appeared. However, it virtually ignores mobile devices. So, this letter proposes a smooth mobile content migration scheme for CCN to provide lower communication overhead and shorter download time.

Kernel biased discriminant analysis (KBDA), as a subspace learning algorithm, has been an attractive approach for the relevance feedback in content-based image retrieval. Its performance, however, still suffers from the “small sample learning” problem and “kernel learning” problem. Aiming to solve these problems, in this paper, we present a new semi-supervised scheme of KBDA (S-KBDA), in which the projection learning and the “kernel learning” are interweaved into a constrained optimization framework. Specifically, S-KBDA learns a subspace that preserves both the biased discriminant structure among the labeled samples, and the geometric structure among all training samples. In kernel optimization, we directly optimize the kernel matrix, rather than a kernel function, which makes the kernel learning more flexible and appropriate for the retrieval task. To solve the constrained optimization problem, a fast algorithm based on gradient ascent is developed. The image retrieval experiments are given to show the effectiveness of the S-KBDA scheme in comparison with the original KBDA, and the other two state-of-the-art algorithms.

Due to an increase in multimedia content and the acceleration of digital convergence, demand for next-generation IPTV service is rapidly growing. IPTV service seamlessly provides both real-time broadcasting and content sharing services on diverse terminals through complex networks. In this paper, a secure and scalable content sharing framework is proposed for next-generation IPTV service. The proposed framework has an advantage over conventional content protection techniques in producing scalable content with transcodable, adjustable, and perceptual security features. Moreover, it ensures end-to-end security over the entire service range based on a single security mechanism. The suitability of the proposed approach is demonstrated experimentally using a practical service scenario with real-world environments. The experiments show that the proposed approach can provide several different levels of content security, from a perceptual level to an almost unintelligible level, while keeping the additional time overhead low. Consequently, it is expected that use of this security technology alone can have a practical contribution in creating new business opportunities for IPTV services.

This paper presents a content-addressable memory (CAM) using a phase-change device. A hierarchical match-line structure and a one-hot-spot block code are indispensable to suppress the resistance ratio of the phase-change device and the area overhead of match detectors. As a result, an 8-nsec 72-bit-parallel-search CAM is implemented using a phase-change-device/MOS-hybrid circuitry, where high and low resistances are higher than 2.3 MΩ and lower than 97 kΩ, respectively, while maintaining one-day retention.

An ability to assess similarity lies close to the core of cognition. Its understanding support the comprehension of human success in tasks like problem solving, categorization, memory retrieval, inductive reasoning, etc, and this is the main reason that it is a common research topic. In this paper, we introduce the idea of semantic differences and commonalities between words to the similarity computation process. Five new semantic similarity metrics are obtained after applying this scheme to traditional WordNet-based measures. We also combine the node based similarity measures with a corpus-independent way of computing the information content. In an experimental evaluation of our approach on two standard word pairs datasets, four of the measures outperformed their classical version, while the other performed as well as their unmodified counterparts.

Various kinds of content replication strategies in pure P2P networks have recently been examined. However, such strategies have not been thoroughly considered in hybrid P2P networks. In a hybrid P2P network, the target content can easily be found because there is a server that controls each peer and its content. Therefore, it is important to decrease futile storage resource consumption, since the data search cost through the network is relatively small. This paper proposes an effective content replication strategy that takes into account storage capacity restrictions. In brief, this method restricts the number of contents replicas possessed by a peer using threshold-based control by relocating or deleting excess replicas. Furthermore, the effectiveness of the proposal is evaluated using computer simulations.

A sanitizable signature scheme allows a semi-trusted party, designated by a signer, to modify pre-determined parts of a signed message without interacting with the original signer. To date, many sanitizable signature schemes have been proposed based on various cryptographic techniques. However, previous works are usually built upon the paradigm of dividing a message into submessages and applying a cryptographic primitive to each submessage. This methodology entails the computation time (and often signature length) in linear proportion to the number of sanitizable submessages. We present a new approach to constructing sanitizable signatures with constant overhead for signing and verification, irrespective of the number of submessages, both in computational cost and in signature size.