Costas Busch Louisiana State University CCW08. Becomes an issue when designing algorithms The output...

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Costas Busch Louisiana State University CCW’08

Transcript of Costas Busch Louisiana State University CCW08. Becomes an issue when designing algorithms The output...

Page 1: Costas Busch Louisiana State University CCW08. Becomes an issue when designing algorithms The output of the algorithms may affect the energy efficiency.

Costas BuschLouisiana State University

CCW’08

Page 2: Costas Busch Louisiana State University CCW08. Becomes an issue when designing algorithms The output of the algorithms may affect the energy efficiency.

Becomes an issue when designing algorithms

The output of the algorithms may affect the energy efficiency

Page 3: Costas Busch Louisiana State University CCW08. Becomes an issue when designing algorithms The output of the algorithms may affect the energy efficiency.

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

Page 4: Costas Busch Louisiana State University CCW08. Becomes an issue when designing algorithms The output of the algorithms may affect the energy efficiency.

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

Page 5: Costas Busch Louisiana State University CCW08. Becomes an issue when designing algorithms The output of the algorithms may affect the energy efficiency.

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

Page 6: Costas Busch Louisiana State University CCW08. Becomes an issue when designing algorithms The output of the algorithms may affect the energy efficiency.

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

Page 7: Costas Busch Louisiana State University CCW08. Becomes an issue when designing algorithms The output of the algorithms may affect the energy efficiency.

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?

Page 8: Costas Busch Louisiana State University CCW08. Becomes an issue when designing algorithms The output of the algorithms may affect the 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?

Page 9: Costas Busch Louisiana State University CCW08. Becomes an issue when designing algorithms The output of the algorithms may affect the energy efficiency.

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?

Page 10: Costas Busch Louisiana State University CCW08. Becomes an issue when designing algorithms The output of the algorithms may affect the energy efficiency.

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?