Throughput-Optimal Broadcast for Time-Varying Directed Acyclic Wireless Multi-hop Networks with Energy Harvesting Constraints

Abstract : In wireless multi-hop networks, a fundamental problem is to disseminate continuous data traffic from a source node to all other network nodes, which is known as the broadcast problem. Such a problem becomes even more complicated in wireless multi-hop networks with energy-harvesting capabilities at nodes when facing the interaction between stochastics of traffic arrivals at the source and randomness of energy-harvesting process at nodes. In such networks, the energy consumable at a node cannot exceed the amount of the energy harvested at the node. In this paper, we investigate the throughput-optimal broadcast problem in time-varying directed acyclic wireless multi-hop networks with such energy harvesting constraints. The topologies of such networks change dynamically with time while satisfying the directed acyclic property and the energy arrival time and harvested amount at a node are random, which causes the consumable energy in each time slot to fluctuate with time. Existing throughput-optimal broadcast algorithms did not consider such energy-harvesting constraints in their designs and therefore their throughput-optimal properties do not hold anymore in such a network. In this paper, we characterize the energy-harvesting uncertainties at nodes by using time-varying per-slot-based supportable transmission rates of wireless links. We consider the time-varying property of supportable link transmission rates caused by energy-harvesting dynamics in the per-slot transmission scheduling and propose an online max-weight broadcast algorithm. We derive a tight upper bound of broadcast capacity of the wireless networks under study in this paper and further prove that our proposed algorithm is throughput-optimal. We evaluate the throughput and latency performance of the proposed algorithm by simulations and the simulation results affirm our theoretical analysis.
 EXISTING SYSTEM :
 ? The metric can be used along existing routing protocols for wireless ad hoc and sensor networks. ? Although there is a large number of potential ambient RF power, the energy of existing EM waves are extremely low because energy rapidly decreases as the signal spreads farther from the source. ? Therefore, in order to scavenge RF energy efficiently from existing ambient waves, the harvester must remain close to the RF source. ? A properly sized wind turbine is used to exploit linear motion coming from wind for generating electrical energy. ? Miniature wind turbines exists that are capable of producing enough energy to power WSN nodes.
 DISADVANTAGE :
 ? We study the problem of broadcasting packets in wireless networks. At each time slot, a network controller activates non-interfering links and forwards packets to all nodes at a common rate; the maximum rate is referred to as the broadcast capacity of the wireless network. ? We impose two additional constraints that improve the understanding of the problem. ? This is non-trivial for the broadcast problem because explicit queueing structure is difficult to maintain in the network due to packet replication. ? However, efficient link activation under network coding remains an open problem.
 PROPOSED SYSTEM :
 • We focus on the energy harvesting components (the energy subsystem) of a EHWSN node, describing abstractions that have been proposed for modeling them. • We give an overview of the different energy predictors proposed in the literature for two popular forms of energy harvesters, namely, solar and wind harvesters. • The effectiveness of the proposed method is measured by comparing the performance of their solution to that of simple energy predictors based on past observations. • A harvesting-aware DVFS (HA-DVFS) algorithm is proposed in to further improve the system performance and energy efficiency of EA-DVFS and AS-DVFS.
 ADVANTAGE :
 ? In this paper, we study the fundamental performance of broadcasting packets in wireless networks. We consider a timeslotted system. ? It is intuitively clear that the policies in the more structured class ?* are easier to describe and analyze, but may yield degraded throughput performance. ? We demonstrate the superior delay performance of our algorithm, as compared to centralized tree-based algorithm, via numerical simulations. ? Studying the performance of a general broadcast policy is difficult because packets are replicated across the network and may be received out of order. ? The design of efficient wireless broadcast algorithms faces several challenges.

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