We present techniques for synchronizing nodes that periodically broadcast content and presence updates to colocated nodes over an ad hoc network, where nodes may exhibit Byzantine malicious behavior. Instead of aligning duty cycles, our algorithms synchronize the periodic transmissions of nodes. This allows nodes to save battery power by switching off their network cards without missing updates from their neighbors. We propose several novel attack classes and show that they are able to disrupt synchronization even when launched by a single attacker. Finally, we devise a rating based algorithm (RBA) that rates neighbors based on the consistency of their behavior. By favoring well-behaved nodes in the synchronization process, we show that RBA quickly stabilizes the synchronization process and reduces the number of lost updates by 85 percent. Our evaluation also shows that all our algorithms are computationally efficient and, for the setup considered, extend the device lifetime by 30 percent over an always-on Wi-Fi scenario.

We study the problem of detecting and eliminating redundancy in a sensor network with a view to improving energy efficiency, while preserving the network's coverage. We also examine the impact of redundancy elimination on the related problem of coverage-boundary detection. We reduce both problems to the computation of Voronoi diagrams, prove and achieve lower bounds on the solution of these problems, and present efficient distributed algorithms for computing and maintaining solutions in cases of sensor failures or insertion of new sensors. We prove the correctness and termination properties of our distributed algorithms, and analytically characterize the time complexity and traffic generated by our algorithms. Using detailed simulations, we also quantify the impact of system parameters such as sensor density, transmission range, and failure rates on network traffic.

In this paper, we study the problem of detecting and eliminating redundancy in a sensor network with a view to improving energy efficiency, while preserving the network's coverage. We also examine the impact of redundancy elimination on the related problem of coverage-boundary detection. We reduce both problems to the computation of Voronoi diagrams, prove and achieve lower bounds on the solution of these problems, and present efficient distributed algorithms for computing and maintaining solutions in cases of sensor failures or insertion of new sensors. We prove the correctness and termination properties of our distributed algorithms, and analytically characterize the time complexity and the traffic generated by our algorithms. Our simulations show that the traffic generated per sensor insertion or removal (failure) experiences a dramatic decrease with an increase in sensor density, (up to 300% when the number of sensors deployed in the same 1000 /spl times/ 1000 m/sup 2/ area increases from 150 to 800), and with an increase in radio transmission range (up to 200% when the sensor's transmission range increases from 70 m to 200 m).

In this paper we introduce the concept of temporal locality of communication for process groups and a hierarchical decision model for dynamic scheduling of process groups. Empirical evidence suggests that, once a member of a process group starts to communicate with other processes in the group, it will continue to do so, while an independent process will maintain its state of isolation for some time. Other instances of inertial behavior of programs are known. Temporal and spatial locality of reference are examples of inertial behavior of programs, exploited by hierarchical storage systems; once a block of information (program or data) is brought into faster storage, it is very likely that it will be referenced again within a short time frame. When process groups exhibit temporal locality of communication, this information can be used to hide the latency of paging and I/O operations, to perform dynamic scheduling to reduce processor fragmentation, and to identify optimal instances of time for checkpointing of process groups. In our scheduling model the supervisory process of a process group collects information about the dynamics of the group and shares it with local and global scheduling agents. © 1998 John Wiley & Sons, Ltd.