Current Issue : January - March Volume : 2015 Issue Number : 1 Articles : 6 Articles
A vector quantizer is a system for encoding the original data to reduce the bits needed for communication and storage saving\nwhile maintaining the necessary fidelity of the data. Signal processing over distributed network has received a lot of attention in\nrecent years, due to the rapid development of sensor network. Gathering data to a central processing node is usually in feasible for\nsensor network due to limited communication resource and power. As a kind of data compression methods, vector quantization\nis an appealing technique for distributed network signal processing. In this paper, we develop two distributed vector quantization\nalgorithms based on the Linde-Buzo-Gray (LBG) algorithm and the self-organization map (SOM). In our algorithms, each node\nprocesses the local data and transmits the local processing results to its neighbors. Each node then fuses the information from the\nneighbors. Our algorithms remarkably reduce the communication complexity compared with traditional algorithms processing all\nthe distributed data in one central fusion node. Simulation results show that both of the proposed distributed algorithms have good\nperformance....
There have been increasing demands for research into multi-channel-based wireless sensor network protocols and applications\nto support requirements such as increased throughput and real-time or reliable transmission. Researchers or developers of these\nprotocols and applications have to simultaneously analyze the exchanged packets for correctness of both their contents and message\nexchange timelines. However, if developers were to use multiple conventional single-channel packet sniffers for this purpose,\ndebugging during development and the verification process becomes extremely tedious and difficult because of the need to check\nthe correctness of the protocols over multiple channels individually. Therefore, we present a multi-channel packet-analysis system\n(MPAS) that helps in debugging and verification for multi-channel protocols or applications. Wireless packets are detected and\ntime stamped by each sniffer module in the MPAS for each channel, and packets are pre processed and transmitted to a GUI-based\nanalyzer, which then parses the received packets and shows them in order.We present the design and implementation results of the\nMPAS and evaluate its performance by comparing it against a widely used packet sniffer....
Wireless sensor networks (WSNs) are an attractive platform for monitoring and measuring physical phenomena. WSNs typically\nconsist of hundreds or thousands of battery-operated tiny sensor nodes which are connected via a low data rate wireless network. A\nWSNapplication, such as object tracking or environmentalmonitoring, is composed of individual taskswhichmust be scheduled on\neach node. Naturally the order of task execution influences the performance of theWSN application. Scheduling the tasks such that\nthe performance is increased while the energy consumption remains low is a key challenge. In this paper we apply online learning to\ntask scheduling in order to explore the tradeoff between performance and energy consumption. This helps to dynamically identify\neffective scheduling policies for the sensor nodes. The energy consumption for computation and communication is represented\nby a parameter for each application task. We compare resource-aware task scheduling based on three online learning methods:\nindependent reinforcement learning (RL), cooperative reinforcement learning (CRL), and exponential weight for exploration\nand exploitation (Exp3). Our evaluation is based on the performance and energy consumption of a prototypical target tracking\napplication.We further determine the communication overhead and computational effort of these methods.\n1. Introduction\nA wireless sensor network (WSN) is an attractive platformfor\nvarious applications including target tracking, environmental\nmonitoring, data aggregation, and smart environments. The\napplication is composed of tasks which need to be executed\nduring the operation on the sensor nodes. The sensor nodes\nare typically supplied by batteries and thus pose strong\nlimitations not only on energy but also on computation,\nstorage, and communication capabilities [1ââ?¬â??4].\nThe scheduling of the individual tasks has a strong\ninfluence on the achievable performance and energy consumption.\nWSNs operate in a dynamic environment where\nthe need for adaptive and autonomous task scheduling is\nwell recognized [5]. Since it is not possible to schedule the\ntasks a priori, online, and resource-aware task scheduling\nis required for a WSN. For determining the next task to\nexecute, the sensor nodes need to consider the impact of each\navailable task on the energy budget and the applicationââ?¬â?¢s performance.\nThere is tradeoff between application performance\nand resource consumption, and the task scheduler of the\nnode should be able to adapt to changes in the environment...
For a wireless sensor network (WSN) with a large number of inexpensive sensor nodes, energy efficiency is the major concern in\ndesigning network structure and related algorithms. If network collects sensor data using mobile sinks, object tracking mechanism\nmust consider the energy efficiency of sensor nodes in the networks as a whole. Recently research works on WSNs with mobile sinks\napply prediction techniques for sink tracking in order to improve tracking precision while keeping the number of active nodes to the\nminimum. In this paper, we analyze existing works for sink tracking in WSNand propose P-LEACH that is cluster-based prediction\ntechnique for WSN with mobile sinks. Simulation results show that P-LEACH performs better than previous techniques in terms\nof energy saving of sensor nodes and data transmission performance....
In mobile SCTP, a mobile terminal has two or more network interfaces and vertical handover occurs when it moves from one\nnetwork to another.The delay due to the handover process and the slow-start phase of SCTP�s congestion control after handover\ncause substantial performance degradation. If the mobile node goes back and forth frequently, excessive handovers occur and\ndata transmission quality deteriorates. In order to provide the required level of QoS for on-going application, the frequency of\nhandovers should be kept minimized. In this paper, we propose a transport layer handover mechanism using the mobile SCTP.We\ntake the QoS requirements of application as the major criterion in deciding path switching. In our mechanism, the mobile node in\noverlapping area does not perform handover if the current network metrics satisfy the QoS requirements of on-going application.\nBoth analytic evaluation and simulation results show that the proposed mechanism significantly improves the throughput by\nsuppressing unnecessary handovers. Our research results can also be applied to distributed mobile sensor networks....
With the promise of cost effective, unobtrusive, and unsupervised continuous monitoring, wireless body sensor networks (WBSNs)\nhave attracted a wide range of monitoring applications such as medical and healthcare, sport activity, and rehabilitation systems.\nMost WBSN�s medical and healthcare applications are real-time and life-critical, which require strict guarantee of quality of service\n(QoS), in terms of latency, and reliability. Reliability in routing plays key role in providing the overall reliability inWBSNs. This paper\npresents reliability aware routing (RAR) for intra-WBSNs that aims to provide high reliability for reliability constraint data packets.\nIt considers the high and dynamic path loss due to body postural movements and temperature rise of the implanted biomedical\nsensor nodes. We have used two network models in this paper: RAR without Relays (RAR) and RAR with Relays (RARR). The\nsimulation results reveal that RARR outperforms the other state-of-the-art schemes while RAR has slightly low reliability at low\ndata rates as compared to RARR but significantly higher than other state-of-the-art schemes....
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