In this paper, we address the problem of scheduling a set of periodic real-time messages in a wireless network with the objective of minimizing the total energy consumption while meeting deadline and reliability const...
详细信息
ISBN:
(纸本)9781424414321
In this paper, we address the problem of scheduling a set of periodic real-time messages in a wireless network with the objective of minimizing the total energy consumption while meeting deadline and reliability constraints. We formally prove that this problem is NP-hard and solve it in two stages. First, we consider a simple model that assumes that the wireless channel is completely reliable and the network is fully provisioned. Using the technique of employing multiple hop-by-hop transmissions instead of a single direct hop transmission as the basis, we prove that the strategy of choosing the hop distances such that they are equidistant is optimal in terms of energy consumption under the deadline constraint. Based on the intuition provided by the optimal strategy, we present heuristic scheduling algorithms for a more realistic wireless channel model and network condition. Our simulation results show that the proposed scheduling algorithms provide significant energy savings over the baseline algorithms
Recent technological advances have opened up several distributed real-time applications involving battery-driven embedded devices with local processing and wireless communication capabilities. Energy management is the...
详细信息
Recent technological advances have opened up several distributed real-time applications involving battery-driven embedded devices with local processing and wireless communication capabilities. Energy management is the key issue in the design and operation of such systems. In this paper, we consider a single-hop networked real-time embedded system where each node supports both dynamic voltage scaling (DVS) and dynamic modulation scaling (DMS) power management techniques to tradeoff time for energy savings. In this model, we address the problem of scheduling periodic complex tasks where each task consists of several precedence constrained message passing sub-tasks. Our contributions towards this problem are twofold. First, we analyze the system level energy-time tradeoffs considering both the computation and communication workloads by defining a novel energy gain metric. We then present static (centralized) and dynamic (distributed) energy gain based slack allocation algorithms which reduce the total energy consumption, while guaranteeing the ready time, deadline and precedence constraints. We compare the performance of the proposed algorithms with several baseline algorithms through simulation studies. Our results show that the proposed algorithms perform significantly better than the baseline algorithms for the simulated conditions. Finally, we identify several interesting energy-aware research problems in the area of networked real-time embedded systems.
This paper proposes the study of a new computation model that attempts to address the underlying sources of performance degradation (e.g. latency, overhead, and starvation) and the difficulties of programmer productiv...
详细信息
The function of natural immune system is to protect the living organisms against invaders/pathogens. Artificial Immune System (AIS) is a computational intelligence paradigm inspired by the natural immune system. Diver...
详细信息
A wind farm typically consists of a large number of individual wind turbine generators (WTGs) connected by an internal electrical network. To study the impact of wind farms on the dynamics of the power system, an impo...
详细信息
This study proposes a new parameter for evaluating longevity of wireless sensor networks after showing that the existing parameters do not properly evaluate the performance of algorithms in increasing longevity. This ...
详细信息
This study proposes a new parameter for evaluating longevity of wireless sensor networks after showing that the existing parameters do not properly evaluate the performance of algorithms in increasing longevity. This study also proposes an ant inspired Collaborative Routing Algorithm for Wireless Sensor Network Longevity (CRAWL) that has scalability and adaptability features required in most wireless sensor networks. Using the proposed longevity metrics and implementing the algorithm in simulations, it is shown that CRAWL is much more adaptive to non-uniform distribution of available energy in sensor networks. The performance of CRAWL is compared to that of a non-collaborative algorithm. Both algorithms perform equally well when the available energy distribution is uniform but when the distribution is non-uniform, CRAWL is found to have 20.2% longer network life. CRAWL performance degraded by just 10.1% when the available energy was unevenly distributed in the sensor network proving the algorithms adaptability.
PSO is a powerful evolutionary algorithm used for finding global solution to a multidimensional problem. Particles in PSO tend to re-explore already visited bad solution regions of search space because they do not lea...
详细信息
PSO is a powerful evolutionary algorithm used for finding global solution to a multidimensional problem. Particles in PSO tend to re-explore already visited bad solution regions of search space because they do not learn as a whole. This is avoided by restricting particles into promising regions through probabilistic modeling of the archive of best solutions. This paper presents hybrids of estimation of distribution algorithm and two PSO variants. These algorithms are tested on benchmark functions having high dimensionalities. Results indicate that the methods strengthen the global optimization abilities of PSO and therefore, serve as attractive choices to determine solutions to optimization problems in areas including sensor networks.
暂无评论