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The Capacity of Energy- Constrained Mobile Networks

This study focuses on modeling the capacity of energy-constrained mobile networks using a combination of base station and vehicle charging. The research presents a network model, charging strategies, and throughput analysis for different scenarios. Realistic implications and future directions are also discussed.

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The Capacity of Energy- Constrained Mobile Networks

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  1. The Capacity ofEnergy-ConstrainedMobile Networks Xiangyu Chen Riheng Jia Xinbing Wang

  2. Contents 1 Introduction 2 Our Work 3 Future Work Conclusion Your Site Here

  3. Introduction 1 Related Work 2 Our contribution 3 Realistic significance Your Site Here

  4. Gupta & Kumar The throughput in fixed ad-hoc network in its best performance is Grossglauser Mobility can increases the capacity to with relay Seung-Woo Ko The capacity can achieve in energy constrained Mobile network using vehicle charging model Related Work Your Site Here

  5. Using Base Station to charge the node in the Mobile Network Combine vehicle and Base Station to the Mobile Network Our Contribution Your Site Here

  6. Proof the througput in variety energy constrained circumstance. Present the parameter's influence on the throughput Realistic significance Your Site Here

  7. Our Work 1 Network model 2 Base Station Charging 3 Combine BS & vehicle Your Site Here

  8. Pc: probabilities that a BS charges a node Pt: a node transmits a packet given the node has at least one unit of energy R:Charging range r:transmission range W:number of Base Station m:number of nodes X: number of node that Base Station can charge. Network model Your Site Here

  9. Two-phase scheduling policy Network model Phase 1.In odd time slots, source can transmit packets to relays or destination Phase 2. source and relay nodes can transmit packets to destination. In each time slot, a node becomes a transmitter with probability q or a receiver with probability 1−q Your Site Here

  10. Interference Transmitter i successfully deliversa packettoreceiver j when the followingconditions aresatisfied: • The distance between them is no more than r. • The distances between node j and the other transmittingnodes are no less than r. Network model Your Site Here

  11. Charging model where Rx={d:E×τ(d)=x} τ(d)is a non-increasing function of d Charging model Your Site Here

  12. Pc the possibility that BS can charge a node given the energy of the node is not full Pt the possibility that node can send a package to another node given the node has at least one energy Base Station Charging Your Site Here

  13. Base Station Charging • Markov Chain π(4) π(2) π(1) π(0) π(3) state that a node have i energy possibility of the steady state that a node have 1 energy Your Site Here

  14. equilibrium Equation Using G conversion,we have Base Station Charging Your Site Here

  15. Pon and as n increase Throughput Base Station Charging if m=O(n) Otherwise if m<O(n) Otherwise Your Site Here

  16. Now suppose that we use vehicle to charge node and vehicle also need Base Station to provide its energy Combine BS & vehicle PBS: probabilities that a BS charges a vehicle Pt: a node transmits a packet given the node has at least one unit of energy pC: probabilities that a vehicle charges a node RBS:BS charging range Rc:Vehicle charging range r:transmission range W:number of Base Station m:number of nodes X: number of node that Base Station can charge. Your Site Here

  17. Combine BS & vehicle • The vehicle's steady state Markov Chain π(4) π(2) π(1) π(0) π(3) state that a vehicle have i energy possibility of the steady state that a vehicle have i energy Your Site Here

  18. Combine BS & vehicle • The node's steady state Markov Chain π(4) π(2) π(1) π(0) π(3) state that a node have i energy possibility of the steady state that a node have i energy Your Site Here

  19. Pon-vehicle Pon-node Combine BS & vehicle W<O(m) & m<O(n) Otherwise Your Site Here

  20. Throughput Combine BS & vehicle if m<O(n) & W<O(m) Otherwise Your Site Here

  21. BS charging Simulation m=O(n) m=O(1) Your Site Here

  22. BS && vehicle charging Simulation m=O(1) W=O(1) m=O(n) W=O(m) Your Site Here

  23. BS && vehicle charging Future Work Sub Text π(4) π(2) π(1) π(0) π(3) Your Site Here

  24. Future Work Sub Text π(4) π(2) π(1) π(0) YourTextHere YourTextHere π(3) If we can solve these Markov Chain above,we can solve the problem of multilevel charging in the condition of BS & vehicle charging. Your Site Here

  25. Q & A Q & A Conclusion Your Site Here

  26. Thank you! LOGO your site here

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