ZebraNet is a mobile, wireless sensor network in which nodes move throughout an environment working to gather and process information about their surroundings [10]. As in many sensor or wireless systems, nodes have critical resource constraints such as processing speed, memory size, and energy supply; they also face special hardware issues such as sensing device sample time, data storage/access restrictions, and wireless transceiver capabilities. This paper discusses and evaluates ZebraNet's system design decisions in the face of a range of real-world constraints. Impala -- ZebraNet's middleware layer --...

Abstract. We present TinyOS, a flexible, application-specific operating system for sensor networks, which form a core component of ambient intelligence systems. Sensor networks consist of (potentially) thousands of tiny, low-power nodes, each of which execute concurrent, reactive programs that must operate with severe memory and power constraints. The sensor network challenges of limited resources, event-centric concurrent applications, and low-power operation drive the design of TinyOS. Our solution combines flexible, fine-grain components with an execution model that supports complex yet safe concurrent operations. TinyOS meets these challenges well and has become the platform of choice for sensor network research; it is in use by over a hundred groups worldwide, and supports a broad range of applications and research topics. We provide a qualitative and quantitative evaluation of the system, showing that it supports complex, concurrent programs with very low memory requirements (many applications fit within 16KB of memory, and the core OS is 400 bytes) and efficient, low-power operation. We present our experiences with TinyOS as a platform for sensor network innovation and applications. 1

In this paper we discuss a selection of promising and interesting research areas in the design of protocols and systemsforwirelessindustrialcommunications.Wehaveselected topicsthathaveeitheremergedashottopicsintheindustrial communicationscommunityinthelastfewyears(likewireless sensornetworks),orwhichcouldbeworthwhileresearchtopicsin thenextfewyears(forexamplecooperativediversitytechniques for error control, cognitive radio/opportunistic spectrum access for mitigation of external interferences).

This paper addresses the following relay sensor placement problem: given the set of duty sensors in the plane and the upper bound of the transmission range, compute the minimum number of relay sensors such that the induced topology by all sensors is globally connected. This problem is motivated by practically considering the tradeoff among performance, lifetime, and cost when designing sensor networks. In our study, this problem is modelled by a NP-hard network optimization problem named Steiner Minimum Tree with Minimum number of Steiner Points and bounded edge length (SMT-MSP). We propose two approximate algorithms, together with their detailed performance analysis. The first one has performance ratio 3 and the second one has performance ratio 2.5.

Abstract—For the first time, this paper presents an analysis of the performance of the IEEE 802.15.4 low power, low data rate wireless standard in relation to medical sensor body area networks. This is an emerging application of wireless sensor networking with particular performance constraints, including power consumption, physical size, robustness and security. In the analysis presented, the star network configuration of the 802.15.4 standard at 2.4 GHz was considered for a body area network consisting of a wearable or desk mounted coordinator outside of the body with up to 10 body implanted sensors. The main consideration in this work was the long-term power consumption of devices, since for practical reasons, implanted medical devices and sensors must function for at least 10 to 15 years without battery replacement. The results show that when properly configured, 802.15.4 can be used for medical sensor networking when configured in non-beacon mode with low data rate asymmetric traffic. Beacon mode may also be used, but with more severe restrictions on data rate and crystal tolerance. Keywords- wireless body area network; wireless sensor network; 802.15.4; power consumption I.

Since the 1990’s, mobile computing has transformed its penetration from niche markets and early prototypes to ubiquity. Personal Digital Assistants (PDAs) evolved from GRiD’s PalmPad and Apple’s Newton in 1993 to the Palm, Handspring, and Microsoft-based models that support the multi-billion dollar industry today. While BellSouth/IBM’s Simon may have been the only mobile phone to offer e-mail connectivity in 1994, almost every modern mobile phone provides data services

We consider the problem of minimizing the energy needed for data fusion in a sensor network by varying the transmission times assigned to different sensor nodes. The optimal scheduling protocol is derived, based on which we develop a low-complexity inverse-log scheduling (ILS) algorithm that achieves nearoptimal energy efficiency. To eliminate the communication overhead required by centralized scheduling protocols, we further derive a distributed inverse-log protocol that is applicable to networks with a large number of nodes. Focusing on large-scale networks with high total data rates, we analyze the energy consumption of the ILS. Our analysis reveals how its energy gain over traditional time-division multiple access depends on the channel and the data-length variations among different nodes.

Abstract—We propose a new iterative, distributed approach for linear minimum mean-square-error (LMMSE) estimation in graphical models with cycles. The embedded subgraphs algorithm (ESA) decomposes a loopy graphical model into a number of linked embedded subgraphs and applies the classical parallel block Jacobi iteration comprising local LMMSE estimation in each subgraph (involving inversion of a small matrix) followed by an information exchange between neighboring nodes and subgraphs. Our primary application is sensor networks, where the model encodes the correlation structure of the sensor measurements, which are assumed to be Gaussian. The resulting LMMSE estimation problem involves a large matrix inverse, which must be solved in-network with distributed computation and minimal intersensor communication. By invoking the theory of asynchronous iterations, we prove that ESA is robust to temporary communication faults such as failing links and sleeping nodes, and enjoys guaranteed convergence under relatively mild conditions. Simulation studies demonstrate that ESA compares favorably with other recently proposed algorithms for distributed estimation. Simulations also indicate that energy consumption for iterative estimation increases substantially as more links fail or nodes sleep. Thus, somewhat surprisingly, sensor network energy conservation strategies such as low-powered transmission and aggressive sleep schedules could actually prove counterproductive. Our results can be replicated using MATLAB code from www.dsp.rice.edu/software. Index Terms—Asynchronous iterations, distributed estimation, graphical models, matrix splitting, sensor networks, Wiener filter. I.

Wireless sensor networks are becoming increasingly important in recent years due to their ability to detect and convey realtime, in-situ information for many civilian and military applications. A fundamental challenge for such networks lies in energy constraint, which poses a performance limit on the achievable network lifetime. We consider a two-tier wireless sensor network and address the network lifetime problem for upper-tier aggregation and forwarding nodes (AFNs). Existing flow routing solutions proposed for maximizing network lifetime require AFNs to split flows to different paths during transmission, which we call multisession flow routing solutions. If an AFN is equipped with a single transmitter/receiver pair, a multisession flow routing solution requires a packet-level power control at the AFN so as to conserve energy, which calls for considerable overhead in synchronization among the AFNs. In this paper, we show that it is possible to achieve the same optimal network lifetime by power control on a much larger timescale with the socalled single-session flow routing solutions, under which the packet-level power control and, thus, strict requirement on synchronization are not necessary. We also show how to perform optimal single-session flow routing when the bit-rate of composite flows generated by AFNs is time-varying, as long as the average bit-rate can be estimated.

A common technique in wireless sensor networks (WSN) is to use multihopping, that is, relaying messages via intermediate nodes. In this work we compare the energy efficiency of single-hop and multihop taking into account circuit energy consumption as well as transmission energy. We consider a simple two-hop case as well as a multihop case for a uniform two-dimensional network of arbitrary size. Contrary to common beliefs, we find that single-hop is superior for all realistic cases covered by our model. Even in comparison to the simple two-hop case single-hop is preferable. Only at very large path losses would multihop be a serious alternative. At present there are however very few WSN radios available that can operate under such conditions. In spite of the relatively simple networks considered we argue that our findings have quite general applicability with strong implications for the choice of routing protocols. Index Terms — Wireless sensor networks, energy efficiency, multihop, routing 1.