Energy Aware Early Detection for Wireless Mesh Networks
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Solution Overview
Problem
Wireless mesh networks face challenges in efficiently managing packet traffic due to limited resources, leading to congestion and energy inefficiency, as existing methods like lazy packet scheduling and RED algorithms do not adequately account for energy conservation and fairness in packet forwarding.
Innovation Solution
The implementation of Energy Aware Early Detection (EAED) which assesses the rate of change of residual battery capacity to decide whether to queue or drop incoming packets, using advanced metrics such as energy assessment, queue length, and packet type to optimize energy conservation and network throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If lazy packet scheduling is used to minimize energy consumption by delaying packet transmission, then energy consumption is reduced, but network throughput and real-time traffic quality deteriorate
Solution Approach 1:
The patent changes the decision parameter from static queue length thresholds to dynamic energy state assessment. By evaluating the rate of change of residual battery capacity (dE/dt), the system adapts packet forwarding decisions based on real-time energy conditions, allowing aggressive forwarding when energy is abundant and conservative dropping when energy is critical, thus resolving the contradiction between energy saving and throughput maintenance
Solution Approach 2:
The patent performs preliminary energy assessment before packet forwarding decisions are made. By pre-evaluating the energy state and rate of change of battery capacity, the system proactively determines whether to forward or drop packets, preventing energy depletion before it occurs while maintaining network functionality, thus balancing energy conservation with throughput requirements
2Reliability
If RED algorithm is used for congestion avoidance by dropping packets based on queue length, then congestion is avoided, but energy consumption is not optimized and fairness among flows is compromised
Solution Approach 1:
The patent transforms the static RED algorithm into a dynamic energy-aware version. Instead of using fixed queue length thresholds for packet dropping, the system continuously monitors battery energy levels and adjusts dropping probability based on the rate of energy depletion. This dynamic adaptation allows the network to maintain congestion avoidance while optimizing energy consumption patterns according to real-time power conditions
Solution Approach 2:
The patent introduces energy state feedback into the packet forwarding decision process. By continuously monitoring battery capacity and its rate of change, and using this feedback to adjust packet dropping behavior, the system creates a closed-loop control mechanism that balances congestion management with energy conservation, improving upon the open-loop nature of traditional RED
3Productivity
If packets are queued for transmission to maintain network throughput, then network throughput is improved, but energy consumption increases and battery depletes faster
Solution Approach 1:
The patent performs preliminary assessment of energy state before committing to packet queuing and transmission. By evaluating the rate of change of battery capacity in advance, the system determines whether sufficient energy is available to sustain high-throughput operation, preventing premature battery depletion while maintaining optimal throughput when energy conditions permit
Data Source
AI summary
An incoming data packet is received, and a rate of change of residual capacity of a portable power supply is determined. From the determined rate of change it is decided to enqueue or drop the incoming data packet. If the decision is to enqueue, the packet is transmitted. If the decision is drop, the packet is deleted without transmitting. Additional factors may be considered in the decision, such as total energy capacity, residual energy capacity, and first and second derivatives of the residual energy capacity. Real time traffic may be treated differently than non real time traffic, and video enhancement layer packets can be weighted to drop more frequently than video base layer packets for the same flow. If used in the network, congestion probe packets are dropped at a rate matched to the rate at which data packets are dropped to give other nodes an accurate view of link quality.