Lossy compression techniques are commonly used by long-term data-gathering applications that attempt to identify trends or other interesting patterns in an entire system since a data packet need not always be completely and immediately transmitted to the sink. In these applications, a nonterminal sensor node jointly encodes its own sensed data and the data received from its nearby nodes. The tendency for these nodes to have a high spatial correlation means that these data packets can be efficiently compressed together using a rate-distortion strategy. This paper addresses the optimal rate-distortion allocation problem, which determines an optimal bit rate of each sensor based on the target overall distortion to minimize the network transmission cost. We propose an analytically optimal rate-distortion allocation scheme, and we also extend it to a distributed version. Based on the presented allocation schemes, a greedy heuristic algorithm is proposed to build the most efficient data transmission structure to further reduce the transmission cost. The proposed methods were evaluated using simulations with real-world data sets. The simulation results indicate that the optimal allocation strategy can reduce the transmission cost to 6~15% of that for the uniform allocation scheme.

The debris flows caused by typhoon Morakot in August 2009 killed more than 600 people and caused US$ 500 million in damages to agriculture and forestry of Taiwan. Many lives can be saved if we can estimate the occurrence of debris flows and issue timely warnings to inhabitants. Previous literatures [1] have shown that rainfall is highly correlated with debris flows. Thus, the first step to debris flow monitoring and warning is to collect high-resolution, real-time precipitation in the debris-flow-prone areas. In this paper we discuss the considerations of designing a low-cost WSN-based rain gauge grid, which provides highresolution mapping of precipitation. Preliminary experimental results are presented.

In this demo, we present SenPro, a profiling tool that profiles the run-time behaviors of a deployed wireless sensor network (WSN). SenPro runs concurrently with the WSN application and provides information of system execution in a minimally intrusive manner, without requiring any modification to the application being observed. We demonstrate, for a broad class of data gathering applications, how SenPro helps the designer to understand the application behavior by collecting and analyzing the metrics at the centralized sink.

Proxy-caching strategies, especially prefix caching and interval caching, are commonly used in video-on-demand (VOD) systems to improve both the system performance and the playback experience of users. However, because these caching strategies are designed for homogeneous clients, they do not perform well in the real world where clients are heterogeneous (i.e., different available network bandwidths and different sizes of client-side buffers). This paper investigates the problems caused by heterogeneous client-side buffers. We analyze the theoretical performance of these caching strategies, and then, derive cost functions to measure the corresponding performance gains. Based on these analytical results, we develop a caching strategy that employs both prefix caching and interval caching to minimize the input bandwidth of a proxy. The simulation results demonstrate that the bandwidth requirements of a proxy implementing our caching strategy are significantly lower compared to adopting prefix caching or interval caching alone.

Layer streaming has received extensive attention due to the highly heterogeneous access to the Internet nowadays. In this paper, we propose a cooperative proxy framework, called layered chaining, for streaming layered videos efficiently. The framework can not only provide adaptive video quality to heterogeneous clients according to their available reception bandwidth but also support near-instantaneous playback service to a large number of clients by utilizing the resources available at proxy servers. Moreover, the system performance can be further improved via the cooperation of the proxies. The simulation results show that the layered chaining scheme achieves considerably fine performance in terms of reject rate, proxy buffer utilization, and server load.

By forwarding the server stream client by client, a chaining-based scheme is a good way to reduce the server streams for streaming applications in well-connected networks. In this paper, we prove that the minimum number of required server streams in such schemes is n-k+1, where n is the number of client requests and k is a value determined by client buffer sizes and the distribution of requests. In addition, we present an optimal chaining algorithm using a dynamic buffer allocation strategy. Compared to existing chaining schemes, our scheme not only utilizes the backward (basic chaining) and/or forward (adaptive chaining) buffer, but also exploits the buffers of other clients in order to extend the chain as much as possible. In this way, more clients can be chained together and served by the same server stream. Our simulation results show that the requirements of the server streams in the presented scheme are much lower those of existing chaining schemes. We also introduce mechanisms for handling VCR functions and fault exceptions in practical applications.

On the basis of the emerging peer-to-peer structure and the characteristics of user behavior, this paper proposes a scalable video delivery scheme, named P2PVD, for large scale video-on-demand application. In P2PVD, two types of orders are permitted: reserved and urgent orders. Reserved orders are encouraged with a lower price policy to smooth the network traffic and the server load. A delay-aware dynamic parallel transmission in the requesting peer is introduced to serve the reserved and urgent orders. The supplying peer is carefully designed based on three priority rules to increase the capacity of P2PVD. Experimental results indicate that P2PVD is scalable.

The performance of streaming caches is not only affected by cache management but also determined by cache cooperation. If caches cooperate together, the desired video may be obtained from other caches thus reducing server load. However, such process increases network traffic between caches. It must be done carefully. This paper proposes a cooperative cache framework to automatically select appropriate cache sources and paths for various network environments. Simulation results demonstrate that the proposed framework is efficient and easy to implement for streaming caches.

Chaining is a promising technique in alleviating the network and the server load by serving numbers of clients in a single server stream. In this scheme, each client temporarily stores the ongoing media stream in the client buffer and forwards it to another client with adequate buffering delay to meet the next client playback time. Therefore, the clients request the same video program can be chained together if the client buffer is large enough to bridge clients' playback time. However, existing chaining schemes do not efficiently exploit the client buffer space. In this paper, we present an optimal chaining algorithm to fully utilize the client buffer space and hence minimize the required server streams. Our performance comparison demonstrates that the optimal chaining scheme significantly reduces the server load over the existing chaining schemes. More importantly, the proposed scheme can integrate the streaming proxy into the video chain, which makes the video chain more reliable and flexible in real systems. This paper also presents the prototype implementation of the optimal chaining based video-on-demand system.

Video-on-Demand (VoD) systems are attractive multimedia services over the Internet. However, conventional VoD systems can not serve many viewers simultaneously because such large-scale services require considerable server load and network bandwidth. This study proposes a cooperative proxy scheme, consisting of a streaming cache and a query protocol revised from Internet Cache Protocol (ICP), to improve performance of large-scale VoD systems. The streaming cache we proposed attempts to serve the most requests with slightly computation overhead In addition, our query protocol further extends service scalability by satisfying requests "as far as possible", although Web proxies prefer "as near as possible". Simulation results demonstrate that our proxy scheme is efficient especially in large-scale VoD systems.

The on-demand multicast [1] is a novel scheme to reduce the video delivery cost for the streaming video applications. Unlike the conventional multicast, this scheme enables the transmission of the multicast data to multiple recipients at distinct times. This property is important for the streaming video applications since the users usually access the video program at different times. To deliver the same multicast data to the recipients at distinct times, the on-demand multicast scheme temporarily caches a sliding window of the incoming stream on a router (or a proxy) and then forwards it on different links at distinct times to generate timevariant outgoing streams. By carefully scheduling the departure time on each router's outgoing streams, a video stream can be distributed to the recipients at their expected times. Based on this scheme, this paper presents three routing algorithms on an asymmetric transmission network model, such as cable systems and ADSL systems. The simulation results indicate that our algorithm offers an outstanding performance in reducing the number of multicast streams and the network bandwidth. In addition, our simulation results are valuable to plan the system resources when deploying the video-on-demand systems.