We study the capacity of static wireless networks, both ad hoc and hybrid, under the Protocol and Physical Models of communication, proposed in [1]. For ad hoc networks with <i>n</i> nodes, we show that under the Physical Model, where signal power is assumed to attenuate as 1/r^α, α > 2, the transport capacity scales as Θ(√<i>n</i>) bit-meters/sec. The same bound holds even when the nodes are allowed to approach arbitrarily close to each other and even under a more generalized notion of the Physical Model wherein the data rate is Shannon's logarithmic function of the SINR at the receiver. This result is sharp since it closes the gap that existed between the previous best known upper bound of O(<i>n</i>^α-1/α) and lower bound of Ω(√n). We also show that any spatio-temporal scheduling of transmissions and their ranges that is feasible under the Protocol Model can also be realized under the Physical Model by an appropriate choice of power levels for appropriate thresholds. This allows the generalization of various lower bound constructions from the Protocol Model to the Physical Model. In particular, this provides a better lower bound on the best case transport capacity than in [1]. For hybrid networks, we consider an overlay of μ<i>n</i> randomly placed wired base stations. It has previously been shown in [6] that if all nodes adopt a common power level, then each node can be provided a throughput of at most Θ(1/log <i>n</i>) to randomly chosen destinations. Here we show that by allowing nodes to perform power control and properly choosing ν(1/log <i>n</i>), it is further possible to provide a throughput of Θ(1) to any fraction <i>f</i>, 0 < <i>f</i> < 1, of nodes. This result holds under both the Protocol and Physical models of communication. On the one hand, it shows that that the aggregate throughput capacity, measured as the sum of individual throughputs, can scale linearly in the number of nodes. On the other hand, the result underscores the importance of choosing minimum power levels for communication and suggests that simply communicating with the closest node or base station could yield good capacity even for multihop hybrid wireless networks.

We analyze the spatial smoothing algorithm of Solis, Borkar and Kumar [1] for clock synchronization over multi-hop wireless networks. In particular, for a model of a random wireless network we show that with high probability the error variance is O(1) as the number of nodes in the network increases. This provides support for the feasibility of time-based computing n large wireless networks. We also provide bounds on the settling time of a distributed algorithm.

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The functional lifetime of a sensor network is defined as the maximum number of times a certain data collection function or task can be carried out without any node running out of energy. The specific task considered in this paper is that of communicating a specified quantity of information from each sensor to a collector node. The problem of finding the communication scheme which maximizes functional lifetime can be formulated as a linear program, under "fluid-like" assumptions on information bits. This paper focuses on analytically solving the linear program for some simple regular network topologies.The two topologies considered are a regular linear array, and a regular two-dimensional network. In the linear case, an upper bound on functional lifetime is derived, as a function of the initial energies and quantities of data held by the sensors. Under some assumptions on the relative amounts of the energies and data, this upper bound is shown to be achievable, and the exact form of the optimal communication strategy is derived. For the regular planar network, upper and lower bounds on functional lifetime, differing only by a constant factor, are obtained.Finally, it is shown that the simple collection scheme of transmitting only to nearest neighbors, yields a nearly optimal lifetime in a scaling sense.0-7803-9201

Providing differentiated Quality of Service (QoS) over unreliable wireless channels is an important challenge for supporting several future applications. We analyze a model that has been proposed to describe the QoS requirements by four criteria: traffic pattern, channel reliability, delay bound, and throughput bound. We study this mathematical model and extend it to handle variable bit rate applications. We then obtain a sharp characterization of schedulability vis-a-vis latencies and timely throughput. Our results extend the results so that they are general enough to be applied on a wide range of wireless applications, including MPEG Variable-BitRate (VBR) video streaming, VoIP with differentiated quality, and wireless sensor networks (WSN).Two major issues concerning QoS over wireless are admission control and scheduling. Based on the model incorporating the QoS criteria, we analytically derive a necessary and sufficient condition for a set of variable bit-rate clients to be feasible. Admission control is reduced to evaluating the necessary and sufficient condition. We further analyze two scheduling policies that have been proposed, and show that they are both optimal in the sense that they can fulfill every set of clients that is feasible by some scheduling algorithms. The policies are easily implemented on the IEEE 802.11 standard. Simulation results under various settings support the theoretical study.

Abstract-With the advent of CMOS cameras, it is now possible to make compact, cheap and low-power image sensors capable of on-board image processing. These embedded vision sensors provide a rich new sensing modality enabling new classes of wireless sensor networking applications. In order to build these applications, system designers need to overcome challanges associated with limited bandwith, limited power, group coordination and fusing of multiple camera views with various other sensory inputs. Real-time properties must be upheld if multiple vision sensors are to process data, communicate with each other and make a group decision before the measured environmental feature changes. In this paper, we present FireFly Mosaic, a wireless sensor network image processing framework with operating system, networking and image processing primitives that assist in the development of FireFly Mosaic, we demonstrate an assisted living application capable of fusing multiple cameras with overlapping views to discover and monitor daily activities in a home. Using this application, we show how an integrated platform with support for time synchronization, a collision-free TDMA link layer, an underlying RTOS and an interface to an embedded vision sensor provides a stable framework for distributed real-time vision processing. To the best of our knowledge, this is the first wireless sensor networking system to integrate multiple coordinating cameras performing local processing.

We obtain improved upper and lower bounds on the best case and random case transport capacities of wireless networks under the Protocol Model of communication in Reference [1]. These results bracket the best case transport capacity to within a factor of ffiffi ffi 8 p for wireless networks on a disk. This is done by identifying larger exclusion regions for receivers. The general result on exclusion regions can also be applied to arbitrary wireless footprints, including those arising from directional antennas, thus obtaining superior bounds for such technologies too.

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