In recent years, the BitTorrent (BT) has been one of the most efficient mechanisms for Peer-to-Peer (P2P) non-realtime content distribution. Many approaches for streaming videos over BitTorrent have been proposed by modifying the piece selection policy to cope with the real time requirement. Most of them provide the continuity of video playback at the cost of the variety of pieces on P2P streaming networks. In this paper, we propose the novel urgency-aware BT streaming mechanism, called UR-Aware, which intends to enhance the video streaming efficiency over BitTorrent on P2P networks by balancing playback continuity and distribution of piece rareness. There are two sets for piece downloading, called Uset and Rset. The Uset contains the most urgent pieces of video playback, while the Rset contains the rarest pieces. Downloading bandwidth of a peer is dynamically allocated to the two sets based on the number of consecutive pieces beyond the playback position in Uset. Furthermore, to implicitly preserve the continuity of pieces for future playback, consecutive k pieces are grouped as a section which would be selected to insert into Rset based on its rareness. The experimental results showed that the UR-Aware has the best performance among other BT streaming approaches in terms of video download time and piece late rate.

In P2P systems, because the buffer space of each peer is limited, most of P2P systems employ the cache-and-relay schemes that require each peer to cache the most recent video stream it receives. As long as the initial part of the video stream remains in its buffer, the peer can then relay the cached stream to late-arriving peers in a pipelining fashion and then the loading of a server is reduced. In our previous research work, we proposed a novel caching scheme for peer-to-peer on-demand streaming, called Dynamic Buffering, which relies on the feature of Multiple Description Coding to gradually reduce the number of cached descriptions in a peer once the buffer is full. In this paper we discuss service availability of a peer with dynamic buffering for various numbers of kinds of forwarded descriptions, and provide detailed analyses on how the number of kinds of forwarded descriptions affects average service availability of a peer. In addition, the mathematical formulas of the reduction of average service availability for various numbers of kinds of forwarded descriptions is derived. Our experiment results showed that the reduction of average service availability is only related to the number of kinds of forwarded descriptions.

In peer-to-peer on-demand streaming networks, the alleviation of server load depends on reciprocal stream sharing among peers. In general, on-demand video services enable clients to watch videos from beginning to the end in a pipeline fashion. As long as a client still caches the initial part of the video, it can provide on-demand service to the subsequent clients without intervention of a server. Therefore, the key challenge is how to maximize the availability of a video for stream relay by keeping the initial part of a video in a peer's buffer as long as possible. In addition, to address the issues of delivering data on lossy network and providing scalable quality of services for clients, the adoption of multiple description coding has been proven as a feasible resolution by much research work. In this paper, we propose a novel caching scheme for P2P on-demand streaming called Balanced Dynamic Buffering with multiple description coding. The proposed balanced dynamic buffering gradually reduce the number of buffered descriptions once the buffer gets full. In addition, peers are grouped based on the number of descriptions cached in its buffer. The intra-group balancing and inter-group balancing are applied for well distributing descriptions and balancing their forwarding bandwidth on peer-to-peer on-demand streaming network. Simulation results showed that the balanced dynamic buffering significantly outperformed other dynamic buffering schemes and the Coop Net.

In general, on-demand video services enable clients to watch videos from beginning to end. As long as clients are able to buffer the initial part of the video they are watching, on-demand service can provide access to the video to the next clients who request to watch it. In our previous research work, we proposed a novel caching scheme for peer-to-peer on-demand streaming, called Dynamic Buffering. The dynamic buffering relies on the feature of Multiple Description Coding to gradually reduce the number of cached descriptions held in a peer's buffers once the buffer is full. In this paper, we proposed three description dropping policies for dynamic buffering, called sequence dropping, m-dropping, and binary dropping. Mathematical formulas of the reduced number of buffer adjustments of descriptions and the reduction of the average number of selectable descriptions for m-dropping and binary dropping by factors of n and m were established in the paper. Experimental results showed that the m-dropping, m=[n/2] generally outperformed m-dropping, m=2 and binary dropping in terms of service availability. Even though the accumulated reduction of buffer adjustments for m-dropping polices was less than that for binary dropping, the average number of selectable descriptions for m-dropping was much greater than that for binary dropping.

In our previous work, we proposed a novel approach to partition sensors on wireless sensor network, called node coverage grouping (NCG), where sensors in the connectivity group are within sensing range of each other, and their collected data are assumed to be similar. Power saving was achieved by alternatively turning on a sensor in a connectivity group for working. We also proved that partitioning n nodes by node coverage grouping into connectivity groups is a NP-hard problem, and proposed a heuristic algorithm of node coverage grouping with the time complexity of O(n3). In this paper, we present two approaches, called periodic probing and next-turn probing, to address the avoidance of blind period for the node coverage grouping. The experimental results showed that the NCG applying the avoidance of blind period would have shorter blind period than two other power saving approaches on wireless sensor network, the Lightweight Deployment-Aware Scheduling (LDAS) and the Probing Environment and Adaptive Sleeping (PEAS). In conclusion, the NCG-next-turn probing outperformed the LDAS and the PEAS with more number of living nodes, more coverage, and shorter blind period with respect to the proceeding of the system lifetime.

The study of wireless Sensor Networks (WSN)recently has drawn a lot of attention. Such networks are composed of a large number of tiny wireless sensors, which have limited calculating capability as well as limited power typically supplied by microelectronics hardware. How to prolong network lifetime while maintaining a sufficient sensing area has been one of the most important issues in WSN research. In a high-density environment of sensor networks, excessive working sensors could cause several problems, such as excessive sensing or channel congestion. In this paper, we present a novel approach to partition sensors in the WSN, called node coverage grouping (NCG). Sensors in the connectivity group are within sensing range of each other, and data collected by sensors in a connectivity group are assumed to be similar. In this paper, we also prove that partitioning n nodes by node coverage grouping into connectivity groups is a NP-hard problem. Then we propose a heuristic algorithm of node coverage grouping with the time complexity of O(n3). The experimental results show that the NCG outperforms the LDAS and the PEAS methods in terms of the number of living nodes, the number of working nodes, and the coverage with the proceeding of system lifetime.

We consider the problem of supporting continuous spatial queries in a new and challenging network environment, namely a Mobile Peer-To-Peer (MP2P) network. Specifically, we propose a distributed technique, called ExtRange, that can efficiently answer continuous moving range queries in a MP2P network. The two key ideas in ExtRange are extended range and safe period. For each query, ExtRange extends the query monitoring region beyond the query range to ensure the accuracy of the query result under the dynamic condition of mobile nodes. Additionally, for each query it monitors, a mobile node computesa safe period, during which the mobile node does not have to update its location with the query node. Through analytical study, we prove that ExtRange guarantees the accuracy for query results when network communication is perfect. Using extensive simulation study, we show that ExtRange delivers high accuracy for query results with low associated costs under realistic simulation settings.

A Location-based Service has to protect user's location and query information to alleviate privacy concerns. Several location and query privacy preserving approaches, based on the concept of k-anonymity and l-diversity, have been proposed in the literature. These approaches assume a trusted anonymizer. Caching has been used as the trusted anonymizer to save communication and computation cost and to enhance the privacy of snapshot and continuous user queries. Such cache designs only provide privacy up to a certain limit and are not designed for multiple points of interest (POI) type queries. We propose a novel cache design and a cache event model that provides significantly higher levels of privacy. We also propose a novel privacy preserving metric which measures the privacy offered by different components (caching, k-anonymity, l-diversity) of the anonymizer which is to the best of our knowledge the first comprehensive privacy measuring metric. We perform several experiments on real world data to evaluate the effectiveness of our cache design in terms of privacy enhancements, computation and communication costs.

In this paper, we relax the restriction of only one designated description forwarded by a peer described in our previously proposed balancing scheme and propose the fine-grained balancing scheme to further improve the scalability of P2P live streaming network based on multiple description coding (MDC) techniques. Like the balancing scheme, the fine-grained balancing scheme is capable of balancing the distribution of descriptions and peer loading by a centralized description allocation scheme. In addition, according to our analysis, its flexibility of selecting desired descriptions and source peers favors the utilization of the aggregate bandwidth of P2P network. The performance study shows that our fine-grained balancing scheme can successfully reduce the consumption of server bandwidth and the rejection rate so that more clients can be served.

In reality, not all users require instant video access. People are used to plan things ahead, surely including when to watch desired videos. This fact creates the new video scheduling paradigm, named scheduled video delivery (SVD). It allures clients to make requests as early as possible in order to increase the flexibility of scheduling and resource utilization based on pricing. In this paper, we propose the multi-channel multicast delivery (MCMD) scheduling algorithm for SVD. MCMD fully utilizes the multi-channel receiving capability of clients to improve the resource utilization and the degree of multicast in delivering continuous media. The case study of scheduling behavior shows that MCMD produces lower rejection rate, higher channel utilization, and shorter delivery time than the existing MEDF and LPF on SVD.

Abstract Video servers are essential in video‐on‐demand and other multimedia applications. In this paper, we present our high‐performance clustered CBR video server, Odyssey. Odyssey is a server connecting PCs with switched Ethernet. It provides efficient support for normal play and interactive browsing functions such as fast‐forward and fast‐backward. We designed a set of algorithms for scheduling, synchronization and admission control, which results in a high utilization of resources. Odyssey is able to deliver a large number of video streams. Copyright © 2003 John Wiley & Sons, Ltd.

No abstract available.

In this paper, we present the performance result and analysis of parallel CBR video servers with conflict-free scheduling algorithms and server synchronization at time slot and time cycle levels.The experimental outcome shows that by relaxing serverlevel synchronization to a time cycle, the conflict-free slot scheduling produces higher stream throughput than the cycle scheduling.