Abstract
More and more Internet of Things (IoT) wireless devices have been providing ubiquitous services over the recent years. Since most of these devices are powered by batteries, a fundamental trade-off to be addressed is the depleted energy and the achieved data throughput in wireless data transmission. By exploiting the rate-adaptive capacities of wireless devices, most existing works on energy-efficient data transmission try to design rate-adaptive transmission policies to maximize the amount of transmitted data bits under the energy constraints of devices. Such solutions, however, cannot apply to scenarios where data packets have respective deadlines and only integrally transmitted data packets contribute. Thus, this paper introduces a notion of weighted throughput, which measures how much total value of data packets are successfully and integrally transmitted before their own deadlines. By designing efficient rate-adaptive transmission policies, this paper aims to make the best use of the energy and maximize the weighted throughput. What is more challenging but with practical significance, we consider the fading effect of wireless channels in both offline and online scenarios. In the offline scenario, we develop an optimal algorithm that computes the optimal solution in pseudo-polynomial time, which is the best possible solution as the problem undertaken is NP-hard. In the online scenario, we propose an efficient heuristic algorithm based on optimal properties derived for the optimal offline solution. Simulation results validate the efficiency of the proposed algorithm.
Highlights
In recent years, we have witnessed more and more Internet of Things (IoT) wireless devices providing ubiquitous services in multiple areas [1]
Industrial wireless sensors may be deployed to collect various important and valuable data in time through wireless transmission; smartphones participating in crowdsensing tasks need to transmit various sensed data to a centric platform meeting the delay requirements of different requesters; wireless smart city and smart home sensors may carry out variety of surveillance and monitoring applications which impose different importance and respective deadlines for data packets in wireless communications, etc
This paper addresses an important theoretical and practical question arised in such scenario, Can we determine properly a set of data packets for delivery and design an energy-efficient rate scheduling policy to maximize the weighted throughput, i.e., the total value of successfully/integrally transmitted packets, without violating the energy constraint?
Summary
We have witnessed more and more Internet of Things (IoT) wireless devices providing ubiquitous services in multiple areas [1]. Industrial wireless sensors may be deployed to collect various important and valuable data in time through wireless transmission; smartphones participating in crowdsensing tasks need to transmit various sensed data to a centric platform meeting the delay requirements of different requesters; wireless smart city and smart home sensors may carry out variety of surveillance and monitoring applications which impose different importance and respective deadlines for data packets in wireless communications, etc. In such applications, data packets could have respective deadlines and diverse values.
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