Scheduling Algorithms for Procrastinators

This paper presents scheduling algorithms for procrastinators, where the speed that a procrastinator executes a job increases as the due date approaches. We give optimal off-line scheduling policies for linearly increasing speed functions. We then explain the computational/numerical issues involved in implementing this policy. We next explore the online setting, showing that there exist adversaries that force any online scheduling policy to miss due dates. This impossibility result motivates the problem of minimizing the maximum interval stretch of any job; the interval stretch of a job is the job's flow time divided by the job's due date minus release time. We show that several common scheduling strategies, including the "hit-the-highest-nail" strategy beloved by procrastinators, have arbitrarily large maximum interval stretch. Then we give the "thrashing" scheduling policy and show that it is a \Theta(1) approximation algorithm for the maximum interval stretch.Comment: 12 pages, 3 figure

Adaptive access and rate control of CSMA for energy, rate and delay optimization

In this article, we present a cross-layer adaptive algorithm that dynamically maximizes the average utility function. A per stage utility function is defined for each link of a carrier sense multiple access-based wireless network as a weighted concave function of energy consumption, smoothed rate, and smoothed queue size. Hence, by selecting weights we can control the trade-off among them. Using dynamic programming, the utility function is maximized by dynamically adapting channel access, modulation, and coding according to the queue size and quality of the time-varying channel. We show that the optimal transmission policy has a threshold structure versus the channel state where the optimal decision is to transmit when the wireless channel state is better than a threshold. We also provide a queue management scheme where arrival rate is controlled based on the link state. Numerical results show characteristics of the proposed adaptation scheme and highlight the trade-off among energy consumption, smoothed data rate, and link delay.This study was supported in part by the Spanish Government, Ministerio de Ciencia e Innovación (MICINN), under projects COMONSENS (CSD2008-00010, CONSOLIDER-INGENIO 2010 program) and COSIMA (TEC2010-19545-C04-03), in part by Iran Telecommunication Research Center under contract 6947/500, and in part by Iran National Science Foundation under grant number 87041174. This study was completed while M. Khodaian was at CEIT and TECNUN (University of Navarra)

From experience with indoor wireless networks: A link quality metric that captures channel memory

With ARQ based link-layer schemes, energy consumption on a link increases with packet retransmissions. We define the inefficiency of a link as the expected number of transmissions before a packet is successfully received on that link. Memory in the packet success process, caused by long indoor coherence times, strongly influences inefficiency. Based on measurements, we build a simple model for the packet success process that incorporates memory and predicts our metric practically and accurately. In particular, inefficiency is asymptotically linear in the memory duration when there is a nonzero probability of a deep fade, and approximately logarithmic otherwise

Energy harvesting communication networks: Optimization and demonstration (The E-CROPS project)

We describe the new European project E-CROPS which was ranked first in the 2012 CHIST-ERA competition. This project has begun its work in February 2013 to develop a system-wide approach to using energy harvesting and smart energy management technologies in communication and mobile devices. The project will examine energy-dependent fundamental limits of communications, together with the timely harvesting, storage and delivery of energy to the computing and communication units of these devices, to achieve an optimal balance between the quality of service, performance, and efficient usage of energy. E-CROPS will combine theoretical modelling and performance analysis with experimental demonstrations bringing together four collaborating teams from France (EURECOM), Spain (CTTC), Turkey (METU) and the UK (Imperial College London). © 2013 IEEE

Kalman prediction based proportional fair resource allocation for a solar powered wireless downlink

Optimization of a Wireless Sensor Network (WSN) downlink with an energy harvesting transmitter (base station) is considered. The base station (BS), which is attached to the central controller of the network, sends control information to the gateways of individual WSNs in the downlink. This paper specifically addresses the case where the BS is supplied with solar energy. Leveraging the daily periodicity inherent in solar energy harvesting, the schedule for delivery of maintenance messages from the BS to the nodes of a distributed network is optimized. Differences in channel gain from the BS to sensor nodes make it a challenge to provide service to each of them while efficiently spending the harvested energy. Based on PTF (Power-Time-Fair), a close-to-optimal solution for fair allocation of harvested energy in a wireless downlink proposed in previous work, we develop an online algorithm, PTF-On, that operates two algorithms in tandem: A prediction algorithm based on a Kalman filter that operates on solar irradiation measurements, and a modified version of PTF. PTF-On can predict the energy arrival profile throughout the day and schedule transmission to nodes to maximize total throughput in a proportionally fair way

Approximation Algorithms for Power-Aware Scheduling of Wireless Sensor Networks with Rate and Duty-Cycle Constraints

We develop algorithms for finding the minimum energy transmission schedule for duty-cycle and rate constrained wireless sensor nodes transmitting over an interference channel. Since traditional optimization methods using Lagrange multipliers do not work well and are computationally expensive given the non-convex constraints, we develop fully polynomial approximation schemes (FPAS) for finding optimal schedules by considering restricted versions of the problem using multiple discrete power levels. We first show a simple dynamic programming solution that optimally solves the restricted problem. For two fixed transmit power levels (0 and P), we then develop a 2-factor approximation for finding the optimal fixed transmission power level per time slot, P opt, that generates the optimal (minimum) energy schedule. This can then be used to develop a (2, 1 + ε)-FPAS that approximates the optimal power consumption and rate constraints to within factors of 2 and arbitrarily small ε \u3e 0, respectively. Finally, we develop an algorithm for computing the optimal number of discrete power levels per time slot (O(1/ε)), and use this to design a (1, 1 + ε)-FPAS that consumes less energy than the optimal while violating each rate constraint by at most a 1 + ε factor. © Springer-Verlag Berlin Heidelberg 2006

Towards a Vibration Energy Harvesting WSN Demonstration Testbed

This paper presents initial results toward the implementation of a wireless sensor network (WSN) demonstration testbed powered up by vibration energy, as part of the E-CROPS project. The testbed uses MicaZ Motes, supplied by AA batteries. The power drawn by Motes in different modes of operation are measured. Design details of an electromagnetic harvester, and experimental results of charging AA batteries with this harvester at 10 Hz vibration generated in the laboratory, are presented

Implementation of Energy-Neutral Operation on Vibration Energy Harvesting WSN

This paper presents a method for realizing energy neutral operation on energy harvesting wireless sensor nodes (WSN) and its implementation, regarding that the available environmental energy is unpredictable and changes over time. The method utilizes adaptive duty cycling which provides energy-neutral operation according to the energy available in the environment and the instantaneous energy state of the node through an energy management circuit. The proposed method is implemented using a MicaZ mote as the WSN and two different vibration-based harvesters: piezoelectric and electromagnetic. The node incorporating a piezoelectric harvester, operates for only 130.5 s with a fixed duty-cycle of 0.21%, and requires an inactive time of 93.5 s for charging. On the other hand, with the proposed strategy, the node achieves energy-neutral operation by self-adjusting to 0.17% duty-cycle. Energy-neutral operation is also demonstrated by incorporating an electromagnetic energy harvester attached to the wrist of a runner: When no energy is available for harvesting, the proposed strategy shows about 64% increment in lifetime before going to sleep mode. These demonstrate that the proposed energy management policy proves to achieve energy-neutral operation in an efficient way