A CAM-based matching system for fast exact pattern matching is implemented on a hardware system with FPGA and ASIC. The system has a simple structure, and does not employ any Central Processor Unit (CPU) as well as complicated computations. We take advantage of Content Addressable Memory (CAM) which has an ability of parallel multi-match mode for designing the system. The system is applied to fast pattern matching with various required search patterns without using search principles. In this paper, the authors present a CAM-based system for fast exact pattern matching on 2-D data.

This letter proposes a new delivery format in order to realize unified transmissions of stereoscopic video contents over a dynamic adaptive streaming scheme. With the proposed delivery format, various forms of stereoscopic video contents regardless of their encoding and composition types can be delivered over the current dynamic adaptive streaming scheme. In addition, the proposed delivery format supports dynamic and efficient switching between 2D and 3D sequences in an interoperable manner for both 2D and 3D digital devices, regardless of their capabilities. This letter describes the designed delivery format and shows dynamic interoperable applications for 2D and 3D mixed contents with the implemented system in order to verify its features and efficiency.

Content addressable memory is widely used for fast lookup table data searching, but it often consumes considerable power. Moreover, designing the suitable content addressable memory architecture for a specific application also consumes lots of time, since the behavioral simulation is often done in the transistor level. SystemC is a system-level modeling language and simulation platform, providing high simulation efficiency for hardware software co-design. Unfortunately, SystemC does not provide the function for estimating power dissipation of a structure design. In this paper, a SystemC-based fast content addressable memory power estimation method is presented for estimating the power dissipation of the match-line circuit, the search-line circuit, and the storage cell array of content addressable memory in the early design stage. The mathematical equations and behavioral patterns are used as the inputs of power estimation model. The simulation results based on 10 Mibench benchmarks show that the simulation time of the proposed method is in average 1233 times faster than that of HSPICE simulator with only 3.51% error rate.

In this paper, we propose a new online authoring tool for e-Learning system to meet the social demands for internationalized higher education. The tool includes two functions – an authoring function for creating video-based content by the instructor, and a viewing function for self-learning by students. In the authoring function, an instructor creates key markings onto the raw video stream to produce virtual video clips related to each slide. With key markings, some parts of the raw video stream can be easily skipped. The virtual video clips form an aggregated video stream that is used to synchronize with the slide presentation to create learning content. The synchronized content can be previewed immediately at the client computer prior to saving at the server. The aggregated video becomes the baseline for the viewing function. Based on aggregated video stream methodology, content editing requires only the changing of key markings without editing the raw video file. Furthermore, video and pointer synchronization is also proposed for enhancing the students' learning efficiency. In viewing function, video quality control and an adaptive video buffering method are implemented to support usage in various network environments. The total system is optimized to support cross-platform and cloud computing to break the limitation of various usages. The proposed method can provide simple authoring processes with clear user interface design for instructors, and help students utilize learning contents effectively and efficiently. In the user acceptance evaluation, most respondents agree with the usefulness, ease-of-use, and user satisfaction of the proposed system. The overall results show that the proposed authoring and viewing tools have higher user acceptance as a tool for e-Learning.

Although shared caches allow the dynamic allocation of limited cache capacity among cores, traditional LRU replacement policies often cannot prevent negative interference among cores. To address the contention problem in shared caches, cache partitioning and application scheduling techniques have been extensively studied. Partitioning explicitly determines cache capacity for each core to maximize the overall throughput. On the other hand, application scheduling by operating systems groups the least interfering applications for each shared cache, when multiple shared caches exist in systems. Although application scheduling can mitigate the contention problem without any extra hardware support, its effect can be limited for some severe contentions. This paper proposes a low cost solution, based on application scheduling with a simple cache insertion control. Instead of using a full hardware-based cache partitioning mechanism, the proposed technique mostly relies on application scheduling. It selectively uses LRU insertion to the shared caches, which can be added with negligible hardware changes from the current commercial processor designs. For the completeness of cache interference evaluation, this paper examines all possible mixes from a set of applications, instead of using a just few selected mixes. The evaluation shows that the proposed technique can mitigate the cache contention problem effectively, close to the ideal scheduling and partitioning.

We study the use of network coding to speed up content distribution in peer-to-peer (P2P) networks. Our goal is to get the underlying reason for network coding's improved performance in P2P content distribution and to optimize resource consumption of network coding. We observe analytically and experimentally that in pure P2P networks, a considerable amount of data is sent multiple times from one peer to another when there are multiple paths connecting those two particular peers. Network coding, on the other hand, when applied at upstream peers, eliminates information duplication on paths to downstream peers, which results in more efficient content distribution. Based on that insight, we propose a network coder placement algorithm which achieves comparable distribution time as network coding, yet substantially reduces the number of encoders compared to a pure network coding solution in which all peers have to encode. Our placement method puts encoders at critical network positions to eliminate information duplication the most, thus, effectively shortens distribution time with just a portion of encoders.

To establish seamless and highly robust content distribution, we proposed the new concept of Inter-Stream Forward Error Correction (FEC), an efficient data recovery method leveraging several video streams. Our previous research showed that Inter-Stream FEC had significant recovery capability compared with the conventional FEC method under ideal modeling conditions and assumptions. In this paper, we design the Inter-Stream FEC architecture in detail with a view to practical application. The functional requirements for practical feasibility are investigated, such as simplicity and flexibility. Further, the investigation clarifies a challenging problem: the increase in processing delay created by the asynchronous arrival of packets. To solve this problem, we propose a pragmatic parity stream construction method. We implement and evaluate experimentally a prototype system with Inter-Stream FEC. The results demonstrate that the proposed system could achieve high recovery performance in our experimental environment.

Lately, access loads on servers are increasing due to larger content size and higher request frequency in content distribution networks. Breadcrumbs (BC), an architecture with guidance information for locating a content cache, is designed to reduce the server load and to form content-oriented network autonomously in cooperation with cached contents over IP network. We also proposed Breadcrumbs+ which solves BC's endless routing loop problem. However, Breadcrumbs takes only a passive approach; BC entries are created only when a content is downloaded and only at routers on the download path but not at any other routers. We expect that active and adaptive control of guidance information with simple complexity improves its performance with keeping scalability. In this paper, we propose Active Breadcrumbs which achieves efficient content retrieval and load-balancing through active and adaptive control of guidance information by cache-nodes themselves. In addition, we show the effectiveness of Active Breadcrumbs through the extensive computer simulation.

The number of users of video on demand (VoD) services has increased dramatically. In VoD services, the demand for content items changes greatly hour to hour. Because service providers are required to maintain a stable service during peak hours, they need to design system resources based on the demand at peak time, so reducing the server load at this time is important. Although multicast delivery, in which multiple users requesting the same content item are supported by one delivery session, is effective for suppressing the server load during peak hours, user response times can increase greatly. A peer-to-peer-assisted delivery system, in which users download content items from other users watching the same content item, is also effective for reducing server load. However, system performance depends on selfish user behavior, and optimizing the usage of system resources is difficult. Moreover, complex operation, i.e., switching the delivery multicast tree or source peers, is necessary to support video cassette recorder (VCR) operation, e.g., fast forward, rewind, and pause. In this paper, we propose to reduce server load without increasing user response time by multicasting popular content items to all users independent of actual requests as well as providing on-demand unicast delivery. Through a numerical evaluation that uses actual VoD access log data, we clarify the effectiveness of the proposed method.

There has been an explosion in wireless devices and mobile data traffic, and cellular network alone is unable to support such fast growing demand on data transmission. Therefore, it is reasonable to add another network to the cellular network to augment the capacity. In fact, the dilemma of cellular network is mainly caused by that the same content is repeatedly transmitted in the network, since many people are interested in the same content. A broadcast network, however, could mitigate this problem and save wireless bandwidth by delivering popular content to multiple clients simultaneously. This paper presents a content dissemination system that combines broadcast and cellular networks. Using the model of Markov Decision Process (MDP), we propose an online optimal scheme to maximize the expected number of clients receiving their interested content, which takes clients' interests and queuing length at broadcast and cellular base stations into full consideration. Simulations demonstrate that the proposed scheme effectively decreases item drop rate at base stations and enhances the average number of clients who receive their interested content.

With the rapid expansion of vector data model application to digital content such as drawings and digital maps, the security and retrieval for vector data models have become an issue. In this paper, we present a vector data-hashing algorithm for the authentication, copy protection, and indexing of vector data models that are composed of a number of layers in CAD family formats. The proposed hashing algorithm groups polylines in a vector data model and generates group coefficients by the curvatures of the first and second type of polylines. Subsequently, we calculate the feature coefficients by projecting the group coefficients onto a random pattern, and finally generate the binary hash from binarization of the feature coefficients. Based on experimental results using a number of drawings and digital maps, we verified the robustness of the proposed hashing algorithm against various attacks and the uniqueness and security of the random key.

The quadtree-based variable block sized prediction makes the biggest contribution for dramatically improved coding efficiency in the new video coding standard named HEVC. However, this technique takes about 75–80% computational complexity of an HEVC encoder. This paper brings forward an adaptive scheme that exploits temporal, spatial and transform-domain features to speed up the original quadtree-based prediction, targeting at high resolution videos. Before encoding starts, analysis on utilization ratio of each coding depth is performed to skip rarely adopted coding depths at frame level. Then, texture complexity (TC) measurement is applied to filter out none-contributable coding blocks for each largest coding unit (LCU). In this step, a dynamic threshold setting approach is proposed to make filtering adaptable to videos and coding parameters. Thirdly, during encoding process, sum of absolute quantized residual coefficient (SAQC) is used as criterion to prune useless coding blocks for both LCUs and 3232 blocks. By using proposed scheme, motion estimation is performed for prediction blocks within a narrowed range. Experiments show that proposed scheme outperforms existing works and speeds up original HEVC by a factor of up to 61.89% and by an average of 33.65% for 4kx2k video sequences. Meanwhile, the peak signal-to-noise ratio (PSNR) degradation and bit increment are trivial.

Recently, the number of users downloading video content on the Internet has dramatically increased, and it is highly anticipated that downloading huge size, rich content such as movie files will become a popular use of the Internet in the near future. The transmission bandwidth consumed by delivering rich content is enormous, so it is urgent for ISPs to design an efficient delivery system that minimizes the amount of network resources consumed. To deliver web content efficiently, a content delivery network (CDN) is often used. CDN providers collocate a huge number of servers within multiple ISPs without being informed of detailed network information, i.e., network topologies, from ISPs. Minimizing the amount of network resources consumed is difficult because a CDN provider selects a server for each request based on only rough estimates of response time. Therefore, an ordinary CDN is not suited for delivering rich content. P2P-based delivery systems are becoming popular as scalable delivery systems. However, by using a P2P-based system, we still cannot obtain the ideal delivery pattern that is optimal for ISPs because the server locations depend on users behaving selfishly. To provide rich content to users economically and efficiently, an ISP itself should optimally provide servers with huge storage capacities at a limited number of locations within its network. In this paper, we investigate the content deployment method, the content delivery process, and the server allocation method that are desirable for this ISP-operated CDN. Moreover, we evaluate the effectiveness of the ISP-operated CDN using the actual network topologies of commercial ISPs.

In this paper, we propose an improved seam merging method for content-aware image resizing. This method merges a two-pixel-width seam element into one new pixel in image reduction and inserts a new pixel between the two pixels in image enlargement. To preserve important contents and structure, our method uses energy terms associated with importance and structure. Our method preserve the main structures by using a cartoon version of the original image when calculating the structure energy. In addition, we introduce a new energy term to suppress the distortion generated by excessive reduction or enlargement in iterated merger or insertion. Experimental results demonstrate that the proposed method can produce satisfactory results in both image reduction and enlargement.

With the wide-spread use of high-speed network connections and high performance mobile/sensor terminals available, new interactive services based on real-time contents have become available over the Internet. In these services, end-nodes (e.g, smart phone, sensors), which are dispersed over the Internet, generates the real-time contents (e.g, live video, sensor data about human activity), and those contents are utilized to support many kinds of human activities seen in the real world. For the services, a new decentralized contents distribution system which can accommodate a large number of content distributions and which can minimize the end-to-end streaming delay between the content publisher and the subscribers is proposed. In order to satisfy the requirements, the proposed content distribution system is equipped with utilizing two distributed resource selection methods. The first method, distributed hash table (DHT)-based contents management, makes it possible for the system to efficiently decide and locate the server managing content distributions in completely decentralized manner. And, the second one, location-aware server selection, is utilized to quickly select the appropriate servers that distribute the streamed contents to all subscribers in real time. This paper considers the performance of the proposed resource selection methods using a realistic computer simulation and shows that the system with the proposed methods has scalability for a large-scale distributed system that attracts a very large number of users, and achieves real-time locating of the contents without degrading end-to-end streaming delay of content.

This paper proposes a scheme for fairness between uplink and downlink in error-prone 802.11 DCF WLANs by differentiating the contention window of AP. While existing schemes consider only collision, the proposed scheme takes into account packet error due to poor channel condition, too. Instead of complex analytical models based on Markov chain processes, a simpler model based on mean value analysis is proposed. It works on 802.11 DCF and so avoids being dependent on TXOP which lacks applicability. A performance evaluation shows that the proposed method can achieve fairness even in error-prone environments without decrease of total throughput when compared with existing schemes.

Content-centric networking (CCN) is one of candidates being spotlighted as the technologies of the future Internet to solve the problems of the current Internet. Since DoS/DDoS attack is the most serious threat to the current Internet, this letter introduces the possibility of DoS/DDoS attack on CCN for the first time. And we introduce an attack method using fake-request packets and propose countermeasures in order to detect and/or react to CCN DoS/DDoS attack, and then analyze the result of our proposal.

In Video on Demand (VoD) services, the demand for content items greatly changes daily over the course of the day. Because service providers are required to maintain a stable service during peak hours, they need to design system resources on the basis of peak demand time, so reducing the server load at peak times is important. To reduce the peak load of a content server, we propose to multicast popular content items to all users independently of actual requests as well as providing on-demand unicast delivery. With this solution, however, the hit ratio of pre-distributed content items is small, and large-capacity storage is required at each set-top box (STB). We can expect to cope with this problem by limiting the number of pre-distributed content items or clustering users based on their viewing histories. We evaluated the effect of these techniques by using actual VoD access log data. We also evaluated the total cost of the multicast pre-distribution VoD system with the proposed two techniques.

As one innovative research that heavily depends on the network virtualization for its realization and deployment on an Internet-scale, we propose an approach to utilize user resources in information-centric network (ICN). We try to fully benefit from the in-network cache that is one attractive feature of ICN by expanding the in-network cache indirectly based on the user resources. To achieve this, in this paper, we focus on how to encourage users to contribute their resources in ICN. Through simulations, we examine a feasibility of our approach and an effect of user participation on the content distribution performance in ICN. We also briefly discuss how the network virtualization technique can be utilized for our research in terms of its evaluation and deployment.

A concurrent FIFO queue is a widely used fundamental data structure for parallelizing software. In this letter, we introduce a novel concurrent FIFO queue algorithm for multicore architecture. We achieve better scalability by reducing contention among concurrent threads, and improve performance by optimizing cache-line usage. Experimental results on a server with eight cores show that our algorithm outperforms state-of-the-art algorithms by a factor of two.