Many birds with one stone: multi-objective approximation algorithms
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Online computation and competitive analysis
Online computation and competitive analysis
Bicriteria network design problems
Journal of Algorithms
On-line analysis of the TCP acknowledgment delay problem
Journal of the ACM (JACM)
Proceedings of the twenty-first annual symposium on Principles of distributed computing
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Control Message Aggregation in Group Communication Protocols
ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Competitive analysis of organization networks or multicast acknowledgement: how much to wait?
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Dynamic TCP Acknowledgment: Penalizing Long Delays
SIAM Journal on Discrete Mathematics
Research challenges for wireless sensor networks
ACM SIGBED Review - Special issue on embedded sensor networks and wireless computing
Latency constrained aggregation in sensor networks
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Automating energy optimization with features
FOSD '10 Proceedings of the 2nd International Workshop on Feature-Oriented Software Development
| Hi-index | 5.23 |
In a sensor network the sensors, or nodes, obtain data and have to communicate these data to a central node. Because sensors are battery powered they are highly energy constrained. Data aggregation can be used to combine data of several sensors into a single message, thus reducing sensor communication costs at the expense of message delays. Thus, the main problem of data aggregation is to balance the communication and delay costs. In this paper we study the data aggregation problem as a bicriteria optimization problem; the objectives we consider are to minimize maximum energy consumption of a sensor and a function of the maximum latency costs of a message. We consider distributed algorithms under a synchronous time model, under an asynchronous time model, and under an almost synchronous time model, where sensor clocks are synchronized up to a small drift. We use competitive analysis to assess the quality of the algorithms.