Cheng-Fu Chou

ST-MAC: Spatial-Temporal MAC Scheduling for Underwater Sensor Networks

Underwater sensor networks (UWSNs) have attracted a lot of attention recently. Since data in UWSNs are transmitted by acoustic signals, the characteristics of a UWSN are different from those of a terrestrial sensor network. In other words, the high propagation delay of acoustic signals in UWSNs causes spatial-temporal uncertainty, and makes transmission scheduling in UWSNs a challenging problem. Hence, in this paper, we propose a spatial-temporal MAC scheduling protocol, called ST-MAC, which is designed to overcome spatial-temporal uncertainty based on TDMA-based MAC scheduling for energy saving and throughput improvement. We construct the spatial-temporal conflict graph (ST-CG) to describe the conflict delays among transmission links explicitly, and model ST-MAC as a new vertex coloring problem of ST-CG. We then propose a novel heuristic, called the traffic-based one-step trial approach (TOTA), to solve the coloring problem. In order to obtain the optimal solution of the scheduling problem, we also derive a mixed integer linear programming (MILP) model. Finally, we present a comprehensive performance study via simulations. The results show that ST-MAC can perform better than existing MAC schemes (such as S-MAC, ECDiG, and T-Lohi) in terms of the network throughput and energy cost.

HCDD: hierarchical cluster-based data dissemination in wireless sensor networks with mobile sink

Finding the routing path for disseminating data to mobile sinks in the wireless sensor networks is a challenging problem due to the random mobility of sinks and the limited resources of sensors, such as energy, storage capacity, and computing capability. Although flooding the location information of mobile sinks seems to be a naive method to find the path between the data source and the mobile sink, it drains much power of the sensor nodes. Thus, we propose a Hierarchical Cluster-based Data Dissemination scheme, named HCDD, to disseminate data to the mobile sink with light control overhead. In HCDD, the sensor nodes are self-organized to find the route without the knowledge of nodes location information. That is, unlike other works, the HCDD can operate without any expensive and power-consuming GPS device used for estimating the location information. The simulation results show that our HCDD scheme can greatly alleviate the control overhead, and, at the same time, achieve longer network lifetime and comparable number of received data with previous works, such as the TTDD-like methods.

Preference-aware content dissemination in opportunistic mobile social networks

As mobile devices have become more ubiquitous, mobile users increasingly expect to utilize proximity-based connectivity, e.g., WiFi and Bluetooth, to opportunistically share multimedia content based on their personal preferences. However, many previous studies investigate content dissemination protocols that distribute a single object to as many users in an opportunistic mobile social network as possible without considering user preference. In this paper, we propose PrefCast, a preference-aware content dissemination protocol that targets on maximally satisfying user preference for content objects. Due to non-persistent connectivity between users in a mobile social network, when a user meets neighboring users for a limited contact duration, it needs to efficiently disseminate a suitable set of objects that can bring possible future contacts a high utility (the quantitative metric of preference satisfaction). We formulate such a problem as a maximum-utility forwarding model, and propose an algorithm that enables each user to predict how much utility it can contribute to future contacts and solve its optimal forwarding schedule in a distributed manner. Our trace-based evaluation shows that PrefCast can produce a 18.5% and 25.2% higher average utility than the protocols that only consider contact frequency or preference of local contacts, respectively.

A coordinated data collection approach: design, evaluation, and comparison

We consider the problem of collecting a large amount of data from several different hosts to a single destination in a wide-area network. This problem is important since improvements in data collection times in many applications such as wide-area upload applications, high-performance computing applications, and data mining applications are crucial to performance of those applications. Often, due to congestion conditions, the paths chosen by the network may have poor throughput. By choosing an alternate route at the application level, we may be able to obtain substantially faster completion time. This data collection problem is a nontrivial one because the issue is not only to avoid congested link(s), but to devise a coordinated transfer schedule which would afford maximum possible utilization of available network resources. Our approach for computing coordinated data collection schedules makes no assumptions about knowledge of the topology of the network or the capacity available on individual links of the network. This approach provides significant performance improvements under various degrees and types of network congestions. To show this, we give a comprehensive comparison study of the various approaches to the data collection problem which considers performance, robustness, and adaptation characteristics of the different data collection methods. The adaptation to network conditions characteristics are important as the above applications are long lasting, i.e., it is likely changes in network conditions will occur during the data transfer process. In general, our approach can be used for solving arbitrary data movement problems over the Internet. We use the Bistro platform to illustrate one application of our techniques.

Design of fault-tolerant large-scale VOD servers: With emphasis on high-performance and low-cost

Recent technological advances in digital signal processing, data compression techniques, and high-speed communication networks have made Video-on-Demand (VOD) servers feasible. A challenging task in such systems is servicing multiple clients simultaneously while satisfying real-time requirements of continuous delivery of objects at specified rates. To accomplish these tasks and realize economies of scale associated with servicing a large user population, a VOD server requires a large disk subsystem. Although a single disk is fairly reliable, a large disk farm can have an unacceptably high probability of disk failure. Furthermore, due to real-time constraints, the reliability requirements of VOD systems are even more stringent than those of traditional information systems. Traditional RAID solutions are inadequate due to poor resource usage. Thus, in this paper, we present alternative schemes which provide a high degree of reliability at low disk storage, bandwidth, and memory costs for on-demand multimedia servers. Moreover, we discuss some of the main issues and trade-offs associated with providing fault tolerance in multidisk VOD systems. We would like to impress upon the reader that one of the main points of this paper is the exposition of trade-offs and issues associated with designing fault-tolerant VOD servers. It is not the case that one fault tolerance scheme is absolutely better than another, but rather that one must understand the trade-offs as well as ones system constraints and then choose a fault tolerance scheme accordingly.

A performance study of dynamic replication techniques in continuous media servers

The stringent requirements of multimedia applications make design of cost-effective and scalable systems dificult; thus, eficient adaptive and dynamic resource management techniques can be of great help in improving perjorniance and scalability characteristics of such systems. In this paper; we focus on threshold-basedpolicies for dynamic resource management in the context of continuous media (CM) servers; we do this without any knowledge of data access patterns and with provisions for full use of VCR functionality. We propose a mathematical model of user behavior and show, through a performance study, that not only does the use of this model in conjunction with dynamic resource management policies improves the system’s performance but that it also facilitates signijicantly reduced sensitivity to changes in: (a) system architecture, (b) workload characteristics, (e) skewness of data access patterns, (d) frequency of changes in data access pattems, and (e) choice of threshold values. We believe that not only is this a desirable property for a CM server; in general, but that furthermore, it suggests the usefulness of these techniques across a wide range of continuous media applications.

Delay-Sensitive Opportunistic Routing for Underwater Sensor Networks

Acoustic transmission, inherent to aquatic environments and used in underwater sensor networks (UWSNs), presents its own challenges in terms of energy consumption, long propagation delay, and available bandwidth. These UWSN challenges make it difficult to directly adapt ideas which have already been proven reliable in open-air networks. End-to-end latency is one of the key elements for delay-sensitive UWSN applications. In this paper, we apply the idea of opportunistic-based routing (OR) for maximizing goodput while meeting end-to-end latency requirements for delay-sensitive UWSN applications. In doing so, we introduce a new metric called EEL|success(Fi), which is the expected end-to-end latency from node i to the destination when at least one forwarder of Fi successfully receives a packet; we then formulate this UWSN OR routing problem as a nonlinear optimization model. To effectively solve this problem, we propose a two-step heuristic algorithm, which is composed of per-node forwarding set determination and packet forwarding prioritization. The results of a performance study show that our scheme outperforms other existing works in terms of network goodput and energy costs.

Joint Design of Asynchronous Sleep-Wake Scheduling and Opportunistic Routing in Wireless Sensor Networks

Designing a lifetime-maximization routing in wireless sensor networks poses a great challenge mainly due to unreliable wireless links and limited power supply. Recently, two natural advantages of opportunistic routing, i.e., path diversity and the improvement of transmission reliability, are exploited to develop a lifetime-extended opportunistic routing for wireless sensor networks. Besides, asynchronous sleep-wake scheduling is an effective mechanism to reduce energy consumption by appropriately arranging sensor nodes to sleep. Hence, in this paper, we propose a joint design of asynchronous sleep-wake schedules and opportunistic routing, called ASSORT, to maximize the network lifetime. Simulation results show that ASSORT effectively achieves network lifetime extension compared with other routing schemes.

Quality-Differentiated Video Multicast in Multirate Wireless Networks

Adaptation of modulation and transmission bit-rates for video multicast in a multirate wireless network is a challenging problem because of network dynamics, variable video bit-rates, and heterogeneous clients who may expect differentiated video qualities. Prior work on the leader-based schemes selects the transmission bit-rate that provides reliable transmission for the node that experiences the worst channel condition. However, this may penalize other nodes that can achieve a higher throughput by receiving at a higher rate. In this work, we investigate a rate-adaptive video multicast scheme that can provide heterogeneous clients differentiated visual qualities matching their channel conditions. We first propose a rate scheduling model that selects the optimal transmission bit-rate for each video frame to maximize the total visual quality for a multicast group subject to the minimum-visual-quality-guaranteed constraint. We then present a practical and easy-to-implement protocol, called QDM, which constructs a cluster-based structure to characterize node heterogeneity and adapts the transmission bit-rate to network dynamics based on video quality perceived by the representative cluster heads. Since QDM selects the rate by a sample-based technique, it is suitable for real-time streaming even without any preprocess. We show that QDM can adapt to network dynamics and variable video-bit rates efficiently, and produce a gain of 2-5 dB in terms of the average video quality as compared to the leader-based approach.

Bistro: a framework for building scalable wide-area Upload applications

Hot spots are a major obstacle to achieving scalability in the Internet. At the application layer, hot spots are usually caused by either (a) high demand for some data or (b) high demand for a certain service. This high demand for data or services, is typically the result of a real-life event involving availability of new data or approaching deadlines; therefore, relief of these hot spots may improve quality of life. At the application layer, hot spot problems have traditionally been dealt with using some combination of (1) increasing capacity; (2) spreading the load over time, space, or both; and (3) changing the workload.We note that the classes of solutions stated above have been studied mostly in the context of applications using the following types of communication (a) one-to-many, (b) many-to-many, and (c) one-to-one. However, to the best of our knowledge there is no existing work on making applications using many-to-one communication scalable and efficient (existing solutions, such as web based submissions, simply use many independent one-to-one transfers). This corresponds to an important class of applications, whose examples include the various upload applications such as submission of income tax forms, conference paper submission, proposal submission through the NSF FastLane system, homework and project submissions in distance education, voting in digital democracy applications, voting in interactive television, and many more. Consequently, the main focus of this paper is scalable infrastructure design for relief of hot spots in wide-area upload applications.The main contributions of this paper are as follows. We state (a) a new problem, specifically, the many-to-one communication, or upload, problem as well as (b) the (currently) fundamental obstacles to building scalable wide-area upload applications. We also propose a general framework, which we term the Bistro system, for a class of solutions to the upload problem. In addition, we suggest a number of open research problems, within this framework, throughout the paper.