1 / 10

Energy-efficient distributed algorithms for wireless ad hoc networks

Energy-efficient distributed algorithms for wireless ad hoc networks. Costas Busch Louisiana State University CCW’08. Energy in distributed algorithms. Becomes an issue when designing algorithms T he output of the algorithms may affect the energy efficiency. Typical assumptions.

woodrow
Download Presentation

Energy-efficient distributed algorithms for wireless ad hoc networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Energy-efficient distributed algorithms for wireless ad hoc networks Costas Busch Louisiana State University CCW’08

  2. Energy in distributed algorithms • Becomes an issue when designing algorithms • The output of the algorithms may affect the energy efficiency

  3. Typical assumptions • Computation power at each node is abundant • Unlimited energy for computations at each node • Computation time at each node does not affect total time complexity • Point to point communication • Messages in local neighborhood can be sent simultaneously • Message delivery dominates time complexity

  4. Typical assumptions continued… • The network is reliable • The network topology does not change • The messages are delivered as expected • Global Synchronization • All nodes can synchronize • A special node initiates the algorithm • The algorithm runs only once • One shot problems

  5. Wireless ad hoc network restrictions • Computation power is limited • Communication is not point-to-point • Requires more energy due to channel interference • The network is unreliable (ad hoc, mobility) • More energy to transfer messages • Global synchronization is not easy • More messages, energy to achieve synchronization • An algorithm may run forever • It continuously consumes energy

  6. Rethink distributed algorithm design • Consider energy consumption when designing algorithms • Do not make strong assumptions • Design algorithms with: • Smaller computation at each node • Low message complexity • Self-stabilizing • Local • Online

  7. Performance metrics Classic metrics: • Number of messages • Total time New metrics: • Max, Average utilization of the nodes • Combination of the above metrics • Number of Messages X Total Time? • What are realistic metrics of performance?

  8. Algorithm’s output affects energy efficiency • Topology Control • Focuses on obtaining sparse connected spanners, • But what is the effect on load balancing? • Routing • Focuses on just obtaining routing paths, • But what is the effect on congestion?

  9. Peer-to-peer • Focus on uniformly distributing and accessing the data • But what about the actual node utilization and actual network paths? • Data aggregation • Focus on minimizing the total aggregation cost, • But how does this affect the max cost at a node? • Facility location • Focus on path distances • But how about the load on each facility?

  10. Simplifications are good, but how realistic are they? • How frequently do uniform disc graphs appear in practice? • Can we afford to ignore maximum node utilization? • Is the computation power at each node abundant?

More Related