Just-in-time dynamic voltage scaling: Exploiting inter-node slack to save energy in MPI programs

Although users of high-performance computing are most interested in raw performance, both energy and power consumption have become critical concerns. As a result, improving energy efficiency of nodes on HPC machines has become important, and the prevalence of power-scalable clusters, where the frequency and voltage can be dynamically modified, has increased.     

End-to-End Energy Management in Networked Real-Time Embedded Systems

Performing end-to-end energy management for the data aggregation application poses certain unique challenges particularly when the computational demands on the individual nodes are significant. In this paper, we address the problem of minimizing the total energy consumption of data aggregation with an end-to-end latency constraint while taking into account both the computational and communication workloads in the network. We consider a model where individual nodes support both Dynamic Voltage Scaling (DVS) and Dynamic Modulation Scaling (DMS) power management techniques and explore the energy-time tradeoffs these techniques offer. Specifically, we make the following contributions in this paper. First, we present an analytical problem formulation for the ideal case where each node can scale its frequency and modulation continuously. Second, we prove that the problem is NP-Hard for practical scenarios where such continuity cannot be supported. We then present a Mixed Integer Linear Programming (MILP) formulation to obtain the optimal solution for the practical problem. Further, we present polynomial time heuristic algorithms which employ the energy-gain metric. We evaluated the performance of the proposed algorithms for a variety of scenarios and our results show that the energy savings obtained by the proposed algorithms are comparable to that of MILP.     

基于单向多汇聚节点的WSN分层路由协议

针对分层无线传感器网络的簇首节点容易成为网络瓶颈制约网络性能的不足,提出一种低能耗的路由协议。采用多汇聚（Sink）节点模式来构建网络,利用RSSI（接收信号强度指示）测出各传感器节点与各Sink节点之间的距离,并依据距离的远近为Sink节点划分作用域。通过传感器节点单向与所属Sink节点通信来降低簇首节点的负担。仿真实验结果表明提出的路由协议能有效克服簇首节点网络瓶颈问题,从而降低网络能耗,提高网络生存时间,对于无线传感器网络应用于大范围数据收集的网络具有重要的价值。     

Energy efficient chain based cooperative routing protocol for WSN

In this paper, we investigate the reduction in total transmission time and the energy consumption of wireless sensor networks using multi-hop data aggregation by forming coordination in hierarchical clustering. Novel algorithm handles wireless sensor network in numerous circumstances as in large extent and high density deployments. One of the major purposes is to collect information from inaccessible areas by using factorization of the area into subareas (clusters) and appointing cluster head in each of the subarea. Coordination and cooperation among the local nodes via relay nodes in local cluster (By forming sub clusters) helped to serve each and every node. Routing is based on the predefined path, proposed by new transmission algorithm. Transmission distance is minimized by using cluster coordinators for inter cluster communication and relay nodes within the cluster. We show by extended simulations that Chain Based Cluster Cooperative Protocol (CBCCP) performs very well in terms of energy and time. To prove it, we compare it with LEACH, SEP, genetic HCR and ERP and found that new protocol consumes six times less energy than LEACH, five times less energy than SEP, four time less energy than genetic HCR and three times less energy than ERP, which further validate our work.     

Overlapping computation and communication of three-dimensional FDTD on a GPU cluster

Large-scale electromagnetic field simulations using the FDTD (finite-difference time-domain) method require the use of GPU (graphics processing unit) clusters. However, the communication overhead caused by slow interconnections becomes a major performance bottleneck. In this paper, as a way to remove the bottleneck, we propose the ‘kernel-split method’ and the ‘host-buffer method’ which overlap computation and communication for the FDTD simulation on the GPU cluster. The host-buffer method in particular enables overlapping without any modifications to the update-kernels that are already in use. We also present theoretical formulas to predict the overlap threshold and the total throughput for each method. By using our overlap methods with 6 GPU nodes, we demonstrate that the total performance of 3D FDTD reaches 92% of a six-fold increase, which is the upper limit that would be reached if there were no communication overhead.     

改进的LEACH协议在井下通信系统中的应用

无线传感器网络由能量受限的节点组成,通过部署这些节点以便收集特定监测区域内的有用信息.基于层次的LEACH协议通过将节点分簇以实现数据融合.随机选择的簇头节点接收到本簇成员的数据后进行融合处理,将结果传输到汇聚节点.避免每个节点都与远距离的汇聚节点直接通信,从而节约能耗.将无线传感器网络应用于井下通信系统,能够提高通信的安全性.LEACH的分簇结构与矿井内分坑道工作的情况相类似,把每个坑道作为一个簇,将多数传感器节点安置在坑道内的固定位置,少量节点随矿工位置移动,再将这些节点采集的数据传输至簇头节点.本文主要针对井下通信系统的特点对现有的LEACH协议进行改进,优化了簇头节点的选举方法,并允许部分节点采用多跳方式与汇聚节点通信,使其更符合矿井结构的要求,从而节约了能耗,并且有效地延长了网络的生存时间.     

Communication styles for parallel systems

Distributed-memory parallel systems rely on explicit message exchange for communication, but the communication operations they support can differ in many aspects. One key difference is the way messages are generated or consumed. With systolic communication, a message is transmitted as it is generated. For example, the result computed by the multiplier is sent directly to the communication subsystem for transmission to another node. With memory communication, the complete message is generated and stored in memory, and then transmitted to its destination. Since sender and receiver nodes are individually controlled, they can use different communication styles. One example of memory communication is message passing: both the sender and receiver buffer the message in memory. These two communication styles place different demands on processor design. This article illustrates each style's effect on processor resources for some key application kernels. We are targeting the iWarp system because it supports both communication styles. Two parallel-program generators, one for each communication style, automatically map the sample programs     

基于传感器网络能量均衡分簇算法仿真研究

研究传感网络能量均衡分簇延长网络寿命问题。针对LEACH算法中簇首分布不均及簇首与基站一跳通信能耗大的问题,造成网络簇头的不均匀分布带来的能耗不均衡问题以及簇头的瓶颈等,为了解决上述问题,提出了一种基于能量高效的无线传感器网络分簇路由算法。算法首先在簇头选择过程中利用节点的能量、邻节点数以及每一轮中簇头的个数等参数设置节点当选簇头的优先度,使簇头均匀地分布在网络中;在簇的组建过程中利用能量参数设置簇的重建条件,达到减小簇的重建频率的目的。     

一种具有提高成簇质量的WSN节能分簇路由算法

通过分析无线传感器网络(Wireless Sensor Networks,WSN)分簇路由协议中簇首节点分布不合理的问题,提出了一种基于节点度数、节点间的相对距离和节点剩余能量的节能分簇路由算法。该算法在选择簇首时,充分考虑节点的度数和节点之间的相对距离,这样选择出的簇首不仅覆盖性能好而且在形成的簇中成员节点和簇首节点间的平均距离短,因此簇内通讯的代价小;同时该算法还考虑了节点的剩余能量,能量低的节点成为簇首的可能性降低。通过这样的方法选择簇首形成的簇提高了成簇的质量,进而提高了网络的整体性能,延长了网络的生存时间。在仿真过程中,本文通过计算得出了簇的理想最优情况,并与仿真结果进行比较,验证了本文算法的合理性。     

Architecture of a Web server accelerator

We describe the design, implementation and performance of a high-performance Web server accelerator which runs on an embedded operating system and improves Web server performance by caching data. It can serve Web data at rates an order of magnitude higher than that which would be achieved by a high-performance Web server running on similar hardware under a conventional operating system such as Unix or NT. The superior performance of our system results in part from its highly optimized communications stack. In order to maximize hit rates and maintain updated caches, our accelerator provides an API which allows application programs to explicitly add, delete, and update cached data. The API allows our accelerator to cache dynamic as well as static data. We describe how our accelerator can be scaled to multiple processors to increase performance and availability. The basic design alternatives include a content router or a TCP router (without content routing) in front of a set of Web cache accelerator nodes, with the cache memory distributed across the accelerator nodes. Content-based routing reduces cache node CPU cycles but can make the front-end router a bottleneck. With the TCP router, a request for a cached object may initially be sent to the wrong cache node; this results in larger cache node CPU cycles, but can provide a higher aggregate throughput, because the TCP router becomes a bottleneck at a higher throughput than the content router. We quantify the throughput ranges in which different designs are preferable. We also examine a combination of content-based and TCP routing techniques. In addition, we present statistics from critical deployments of our accelerator for improving performance at highly accessed Sporting and Event Web sites hosted by IBM.     

Design and Implementation of an Agent Home Scheme Strategy for Prefetch-Based DSM Systems

In recent years, cluster computing has been widely investigated and there is no doubt that it can provide a cost-effective computing infrastructure by aggregating computational power, communication, and storage resources. Moreover, it is also considered to be a very attractive platform for low-cost supercomputing. Distributed shared memory (DSM) systems utilize the physical memory of each computing node interconnected in a private network to form a global virtual shared memory. Since this global shared memory is distributed among the computing nodes, accessing the data located in remote computing nodes is an absolute necessity. However, this action will result in significant remote memory access latencies which are major sources of overhead in DSM systems. For these reasons, in order to increase overall system performance and decrease this overhead, a number of strategies have been devised. Prefetching is one such approach which can reduce latencies, although it always increases the workload in the home nodes. In this paper, we propose a scheme named Agent Home Scheme. Its most noticeable feature, when compared to other schemes, is that the agent home distributes the workloads of each computing nodes when sending data. By doing this, we can reduce not only the workload of the home nodes by balancing the workload for each node, but also the waiting time. Experimental results show that the proposed method can obtain about 20% higher performance than the original JIAJIA, about 18% more than History Prefetching Strategy (HPS), and about 10% higher than Effective Prefetch Strategy (EPS).     

一种节能的无线传感器网络分簇算法

针对低功耗自适应聚类层次算法存在的能量问题和簇头瓶颈问题,提出一种节能的无线传感器网络分簇算法,在簇头的选择过程中利用节点能量、邻节点数等参数设置节点当选簇头的优先度,使簇头的分布更均匀。在簇的组建过程中设置能量阈值作为簇的重建条件,减小簇的重建频率,同时采用单跳与多跳结合的数据传输模型,解决网络中的热点、热区问题。仿真实验结果表明,该算法能够有效利用能量,提高网络的稳定性,均衡网络的能量消耗,延长网络寿命,使网络具有更好的延展性、收敛性和安全性。     

一种基于多权值的低能耗WSNs分簇协议

延长网络的生命周期、有效降低节点的能量消耗是无线传感器网络(WSNs)路由研究的重点;针对LEACH协议的簇头选举不合理和和簇成员仅依据自身通信代价选择簇头导致节点能耗不均衡,网络能量利用率低的问题,提出了一种基于多权值的低能耗分簇算法,它综合考虑了候选簇头的剩余能量、节点已当选簇头次数和当前网络簇头个数等多个因素;仿真实验表明,改进协议有效地降低了节点的总能量消耗、提高了网络节点的存活数目,延长了网络的生命周期。     

Topology optimisation for energy management in underwater sensor networks

In general, battery-powered sensors in a sensor network are operable as long as they can communicate sensed data to a processing node. In this context, a sensor network has two competing objectives: (1) maximisation of the network performance with respect to the probability of successful search for a specified upper bound on the probability of false alarms, and (2) maximisation of the network’s operable life. As both sensing and communication of data consume battery energy at the sensing nodes of the sensor network, judicious use of sensing power and communication power is needed to improve the lifetime of the sensor network. This paper presents an adaptive energy management policy that will optimally allocate the available energy between sensing and communication at each sensing node to maximise the network performance subject to specified constraints. Under the assumptions of fixed total energy allocation for a sensor network operating for a specified time period, the problem is reduced to synthesis of an optimal network topology that maximises the probability of successful search (of a target) over a surveillance region. In a two-stage optimisation, a genetic algorithm-based meta-heuristic search is first used to efficiently explore the global design space, and then a local pattern search algorithm is used for convergence to an optimal solution. The results of performance optimisation are generated on a simulation test bed to validate the proposed concept. Adaptation to energy variations across the network is shown to be manifested as a change in the optimal network topology by using sensing and communication models for underwater environment. The approximate Pareto-optimal surface is obtained as a trade-off between network lifetime and probability of successful search over the surveillance region.     

基于能量树的无线传感器网络密钥管理方案

有效的密钥管理方案是实现传感器网络安全通信的前提。针对分簇式无线传感器网络,提出一种基于能量树的密钥管理方案。将网络中节点按树型结构进行管理,并将每个节点的能量值作为树中各边的权值,树根按权值分发不同的秘密信息。簇头间通信密钥借助Blom矩阵的思想生成。分析表明,该方案有效地节省了节点的能量,并提供了较强的可扩展性、节点的抗捕获性和网络的可靠性等安全性能。     

Optimization power consumption model of reliability-aware GPU clusters

Power controlling on reliability-aware GPU clusters with dynamically variable voltage and speed is investigated as combinatorial optimization problem, namely the problem of minimizing task execution time with energy consumption constraint and the problem of minimizing energy consumption with system reliability constraint. The two problems have applied in general multiprocessor computing and real-time multiprocessing systems where energy consumption and system reliability both are important. These problems which emphasize the trade-off among performance, power and reliability have not been well studied before. In this research, a novel power control model is built based on Model Prediction Control theory. Maximum Entropy Method is used to determine partial ordering relation of control variable and to identify the quality of solutions. Our controller can cap the redundant energy consumption by dynamically transforming energy states of the nodes in GPU cluster. We compare our controller with the control scheme, which does not consider the system reliability. The experimental results demonstrate that the proposed controller is more reliable and valuable.     

水声传感器网络中的节能路由协议改进算法

在大规模三维水声传感器网络中,针对节点能耗和网络传输效率的问题,本文基于节点定位和LEACH算法,提出了一种适用于水声通信传感器网络路由算法,该算法采用定位、聚类、唤醒和排列的思想,首先通过定位,确定节点的位置信息,再通过聚类方法,使水下的节点分成不同的簇,形成节点休眠及唤醒的单元.在数据通信过程中,通过及时唤醒簇单元,使需要利用的簇节点及时被唤醒,处于活跃状态,而暂时不被需要的节点进行休眠,从而达到节能的效果.而在簇内传输时,考虑了节点的剩余能量信息,选择最优节点进行信息传输.仿真实验表明,该算法能够提高网络的整体寿命时间.     

一种基于区域分裂与合并的势博弈网络拓扑控制算法

现有无线传感器网络拓扑控制算法在传感器节点部署密集或稀疏区域存在网络拓扑链路冗余、个别节点负载过重、瓶颈节点和网络生命周期短等问题。针对这些问题,提出一种基于区域分裂与合并的势博弈网络拓扑控制算法,该算法首先划分目标区域并随机抛洒传感器节点,在每个子区域内进行博弈并选出簇首节点,利用区域分裂与合并思想,在节点密集区域进行分割再博弈,防止部分节点负载过大,在节点稀疏区域利用权重链路进行合并,防止出现瓶颈节点以保障网络连通;然后对所有簇首节点实施二次势博弈生成簇首拓扑结构连接各子区域。仿真结果表明,该算法能够有效缓解节点负载,均衡节点能耗,延长网络生命周期。     

Adaptive,transparent CPU scaling algorithms leveraging inter-node MPI communication regions

Although users of high-performance computing are most interested in raw performance, both energy and power consumption have become critical concerns. Because the CPU is often the major power consumer, some microprocessors allow frequency and voltage scaling, which enables a system to efficiently reduce CPU performance and power. When the CPU is not on the critical path, such dynamic frequency and voltage scaling can produce significant energy savings with little performance penalty.This paper presents an MPI runtime system that dynamically reduces CPU frequency and voltage during communication phases in MPI programs. It dynamically identifies such phases and, without a priori knowledge, selects the CPU frequency in order to minimize energy-delay product. All analysis and subsequent frequency and voltage scaling is within MPI and so is entirely transparent to the application. This means that the large number of existing MPI programs, as well as new ones being developed, can use our system without modification. Results show that the median reduction in energy-delay product for twelve benchmarks is 8%, the median energy reduction is 11%, and the median increase in execution time increase is only 2%.     

面向物联网的改进PBFT共识算法

随着物联网的发展,高效的共识算法是区块链技术应用于物联网的关键.针对实用拜占庭容错(practical Byzantine fault tolerance, PBFT)算法在物联网场景中通信次数多、未考虑共识功耗、共识时延高等问题,本文提出了一种基于二分K均值算法的改进PBFT共识算法(binary K-means practical Byzantine fault tolerance algorithm,BK-PBFT).首先,获取节点地理坐标并计算节点综合评价值,通过二分K均值算法将节点划分为一个双层多中心聚类集群.然后,先在下层集群再在上层集群对区块进行PBFT共识.最后,集群验证执行并存储区块,完成共识.此外,本文证明了当节点均匀分布在每个簇时算法通信次数可以达到最少,以及通信次数最少时的最优聚类数.分析与仿真结果表明,本文算法可以有效减少通信次数、降低共识功耗和共识时延.