Localizing objects in large-scale cyber- physical systems

We use the term Cyber-Physical Systems to refer to large-scale distributed sensor systems. Locating the geographic coordinates of objects of interest is an important problemin such systems. We present a new distributed approach to localize objects and events of interest in time complexity independent of number of nodes

Highly scalable aggregate computations in cyber-physical systems: physical environment meets communication protocols

In this paper, we focus on large-scale and dense Cyber- Physical Systems, and discuss methods that tightly integrate communication and computing with the underlying physical environment. We present Physical Dynamic Priority Dominance ((PD)2) protocol that exemplifies a key mechanism to devise low time-complexity communication protocols for large-scale networked sensor systems. We show that using this mechanism, one can compute aggregate quantities such as the maximum or minimum of sensor readings in a time-complexity that is equivalent to essentially one message exchange. We also illustrate the use of this mechanism in a more complex task of computing the interpolation of smooth as well as non-smooth sensor data in very low timecomplexity

Bandwidth allocation in hexagonal wireless sensor networks for real-time communications

We present an algorithm for bandwidth allocation for delay-sensitive traffic in multi-hop wireless sensor networks. Our solution considers both periodic as well as aperiodic real-time traffic in an unified manner. We also present a distributed MAC protocol that conforms to the bandwidth allocation and thus satisfies the latency requirements of realtime traffic. Additionally, the protocol provides best-effort service to non real-time traffic. We derive the utilization bounds of our MAC protocol

On Scheduling and Real-Time Capacity of Hexagonal Wireless Sensor Networks

Since wireless ad-hoc networks use shared communication medium, accesses to the medium must be coordinated to avoid packet collisions. Transmission scheduling algorithms allocate time slots to the nodes of a network such that if the nodes transmit only during the allocated time slots, no collision occurs. For real-time applications, by ensuring deterministic channel access, transmission scheduling algorithms have the added significance of making guarantees on transmission latency possible. In this paper we present a distributed transmission scheduling algorithm for hexagonal wireless ad-hoc networks with a particular focus on Wireless Sensor Networks. Afforded by the techniques of ad-hoc networks topology control, hexagonal meshes enable trivial addressing and routing protocols. Our transmission scheduling algorithm constructs network-wide conflictfree packet transmission schedule for hexagonal networks, where the overhead of schedule construction in terms of message exchanges is zero above and beyond that for topology control and other network control related functions. Furthermore, the schedule is optimal in the sense that the bottleneck node does not idle. We also present an implicit clock synchronization algorithm to facilitate scheduling. We derive the real time capacity of our scheduling algorithm. We present evaluations of our scheduling algorithm in the presence of topological irregularities using simulation

Energy-conserving data cache placement in sensor networks

Wireless sensor networks hold a very promising future. The nodes of wireless sensor networks (WSN) have a small energy supply and limited bandwidth available. Since radio communication is expensive in terms of energy consumption, the nodes typically spend most of their energy reserve on wireless communication (rather than on CPU processing) for data dissemination and retrieval. Therefore, the role of energy conserving data communication protocols and services in WSN can not be overemphasized. Caching data at locations that minimize packet transmissions in the network reduces the power consumption in the network, and hence extends its lifetime. Finding locations of the nodes for caching data to minimize communication cost corresponds to finding the nodes of a weighted Minimum Steiner tree whose edge weights depend on the edge’s Euclidean length and its data traffic rate. We call this tree a Steiner Data Caching Tree (SDCT). We prove that an optimal SDCT is binary, and that at-least two of the three internal angles formed at the Steiner points are equal. We derive expressions that determine the exact location of a Steiner point for a set of three nodes based on their location and their data refresh rate requirements. Based on these (optimality) results, we present a dynamic distributed energy-conserving application-layer service for data caching and asynchronous multicast. We present the results of simulation of our service that verifies its power saving properties

A distributed algorithm for hexagonal topology formation in wireless sensor networks

Hexagonal wireless sensor network refers to a network topology where a subset of nodes have six peer neighbors. These nodes form a backbone for multi-hop communications. In a previous work, we proposed the use of hexagonal topology in wireless sensor networks and discussed its properties in relation to real-time (bounded latency) multi-hop communications in large-scale deployments. In that work, we did not consider the problem of hexagonal topology formation in practice - which is the subject of this research. In this paper, we present a decentralized algorithm that forms the hexagonal topology backbone in an arbitrary but sufficiently dense network deployment. We implemented a prototype of our algorithm in NesC for TinyOS based platforms. We present data from field tests of our implementation, collected using a deployment of fifty wireless sensor nodes