Directed diffusion: a scalable and robust communication paradigm for sensor networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Data Gathering Algorithms in Sensor Networks Using Energy Metrics
IEEE Transactions on Parallel and Distributed Systems
Simultaneous optimization for concave costs: single sink aggregation or single source buy-at-bulk
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
The Impact of Data Aggregation in Wireless Sensor Networks
ICDCSW '02 Proceedings of the 22nd International Conference on Distributed Computing Systems
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Flexible power scheduling for sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Energy-balanced task allocation for collaborative processing in wireless sensor networks
Mobile Networks and Applications
TAG: a Tiny AGgregation service for Ad-Hoc sensor networks
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Fast distributed algorithm for convergecast in ad hoc geometric radio networks
Journal of Parallel and Distributed Computing - Special issue: Algorithms for wireless and ad-hoc networks
MauveDB: supporting model-based user views in database systems
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Wireless Communications & Mobile Computing - Advances in Resource-Constrained Device Networking
Distributed Minimal Time Convergecast Scheduling for Small or Sparse Data Sources
RTSS '07 Proceedings of the 28th IEEE International Real-Time Systems Symposium
Quick convergecast in ZigBee beacon-enabled tree-based wireless sensor networks
Computer Communications
A data collection protocol for real-time sensor applications
Pervasive and Mobile Computing
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We consider the convergecast problem in wireless sensor networks where readings generated by each sensor node are to reach the sink. Since a sensor reading can usually be encoded in a few bytes, more than one reading can readily fit into a standard transmission packet. We assume that any such packet consumes one unit of energy every time it hops from a node to a neighbor regardless of the total size of the readings in it. Our objective is to minimize the total energy consumed to send all the readings to the sink. Consequently, we ask the question: can we pack the readings in common routes to minimize the number of hops? It is quite elementary to see that this problem is NP-hard when the size of the readings are arbitrary via reductions from bin packing or set partition. We study the simple version with readings normalized to 1 byte in length. However, we make no assumptions on the underlying graph. We show this to be NP-hard by way of a reduction from Set Cover. We study a class SPEP of distributed algorithms that is completely defined by two properties. Firstly, the packets hop along some shortest path to the sink. Secondly, given all the readings that enter into a node, it sends out as many fully packed packets as possible followed by at most one partial packet --- the elementary packing property. We show that any algorithm in this class is (2−3/2k)-approximate where k ≥ 2 is the size of a data packet in bytes. We additionally show that this class is optimal when the underlying sensor network is a tree or grid topology. Our main technical contribution is a lower bound. We show that no algorithm that either follows the shortest path or packs in an elementary manner is a (2 − ε)-approximation, for any fixed ε 0.