Hash tables – which map “keys ” onto “values” – are an essential building block in modern software systems. We believe a similar functionality would be equally valuable to large distributed systems. In this paper, we introduce the concept of a Content-Addressable Network (CAN) as a distributed infrastructure that provides hash table-like functionality on Internet-like scales. The CAN is scalable, fault-tolerant and completely self-organizing, and we demonstrate its scalability, robustness and low-latency properties through simulation.

For many years, scalable routing for wireless communication systems was a compelling but elusive goal. Recently, several routing algorithms that exploit geographic information (e.g., GPSR) have been proposed to achieve this goal. These algorithms refer to nodes by their location, not address, and use those coordinates to route greedily, when possible, towards the destination. However, there are many situations where location information is not available at the nodes, and so geographic methods cannot be used. In this paper we define a scalable coordinate-based routing algorithm that does not rely on location information, and thus can be used in a wide variety of ad hoc and sensornet environments. 1.

this paper: We propose a novel data dissemination method, DCS, and show where it outperforms other approaches

Recent peer-to-peer (P2P) networks, represented by CAN, Chord, and Pastry, offer an administration-free and faulttolerant application-level overlay network. For these systems to function efficiently, they must make effective use of the underlying network topology. Existing

Gossip algorithms for aggregation have recently received significant attention for sensor network applications because of their simplicity and robustness in noisy and uncertain environments. However, gossip algorithms can waste significant energy by essentially passing around redundant information multiple times. For realistic sensor network model topologies like grids and random geometric graphs, the inefficiency of gossip schemes is caused by slow mixing times of random walks on those graphs. We propose and analyze an alternative gossiping scheme that exploits geographic information. By utilizing a simple resampling method, we can demonstrate substantial gains over previously proposed gossip protocols. In particular, for random geometric graphs, our algorithm computes the true average to accuracy 1/n a using O(n 1.5 √ log n) radio transmissions, which reduces the energy consumption by a algorithms. q n factor over standard gossip log n

Sensornets are large-scale distributed sensing networks comprised of many small sensing devices equipped with memory, processors, and short-range wireless communication. Making effective use of sensornet data will require scalable, self-organizing, and energy-efficient data dissemination algorithms. Recent work has identified data-centric routing as one such method. In this paper we suggest that a companion method, data-centric storage, may also be a useful approach.

Wireless sensor networks are an emerging area of research interest with a number of compelling potential applications. By architecting sensor networks as virtual databases, we can provide a well-understood nonprocedural programming interface suitable to data management, allowing the community to realize sensornet applications rapidly. We argue here that in order to achieve an energy-efficient and useful implementation, query processing operators should be implemented within the sensor network, and that approximate query results will play a key role. We observe that innetwork implementations of database operators require novel data-centric routing mechanisms, as well as a reconsideration of traditional network and database interface layering.

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Consider a large-scale wireless sensor network of n nodes, where a fraction k out of n generate data packets of global interest. Assuming that the individual nodes have limited storage and computational capabilities, we address the problem of how to enable ubiquitous access to the distributed data packets. Specifically, we assume that each node can store at most one data packet, and study the problem of diffusing the data so that by querying any k nodes, it is possible to retrieve all the k data packets of interest (with high probability). We introduce a class of erasure codes and show how to solve this problem efficiently in a completely distributed and robust way. Specifically we show that we can efficiently diffuse the data by “prerouting” only O(ln n) packets per data node to randomly selected storage nodes. By using the proposed scheme, the distributed data becomes available “at the fingertips” of a potential data collector located anywhere in the network.

Recent P2P systems, represented by Oceanstore and PAST, offer an administration-free and fault-tolerant storage utility. Nodes in these systems collectively contribute towards a storage space, in a self-organizing fashion. While elegant from a theoretical perspective, they can be improved in three important areas: (i) low maintenance cost; (ii) the ability to make discriminative use of the nodes in the system that has different capacity and resource constraints; (iii) the ability to adapt to the underlying network conditions and the applications' needs. In this