Dynamic partner identification in mobile agent-based distributed job workflow execution

This paper is concerned with the design, implementation, and evaluation of algorithms for communication partner identification in mobile agent-based distributed job workflow execution. We first describe a framework for distributed job workflow execution over the Grid: the Mobile Code Collaboration Framework (MCCF). Based on the study of agent communications during a job workflow execution on MCCF, we identify the unnecessary agent communications that degrade the system performance. Then, we design a novel subjob grouping algorithm for preprocessing the job workflow's static specification in MCCF. The obtained information is used in both static and dynamic algorithms to identify partners for agent communication. The mobile agent dynamic location and communication based on this approach is expected to reduce the agent communication overhead by removing unnecessary communication partners during the dynamic job workflow execution. The proof of the dynamic algorithm's correctness and effectiveness are elaborated. Finally, the algorithms are evaluated through a comparison study using simulated job workflows executed on a prototype implementation of the MCCF on a LAN environment and an emulated WAN setup. The results show the scalability and efficiency of the algorithms as well as the advantages of the dynamic algorithm over the static one.     

基于移动代理的工作流原型研究与设计

快速发展的移动代理和网格技术给工作流提供了新的集成各种分布式资源的计算环境。传统的工作流架构有很多弱点,比如在动态环境中缺少灵活性等。提出了一个集成Web Services,网格,工作流和移动代理技术的分布式工作流架构,可以通过移动代理间的通讯来达到工作流之间协同工作,而且这个架构增强了工作流的灵活性和可靠性,以这个新的模型为基础实现了一个具体的工作流工作站,且可实现系统的安全使用。     

Automatic distributed workflow generation with GridMD library

GridMD is a C++ class library intended for constructing simulation applications and running them in distributed environments. The library abstracts away from details of distributed environments, so that almost no knowledge of distributed computing is required from a physicist working with the library. She or he just uses GridMD function calls inside the application C++ code to perform parameter sweeps or other tasks that can be distributed at run-time. In this paper we briefly review the GridMD architecture. We also describe the job manager component which submits jobs to a remote system. The C++ source code of our PBS job manager may be used as a standalone tool and it is freely available as well as the full library source code. As illustrative examples we use simple expression evaluation codes and the real application of Coulomb cluster explosion simulation by Molecular Dynamics.     

Precise execution offloading for applications with dynamic behavior in mobile cloud computing

In order to accommodate the high demand for performance in smartphones, mobile cloud computing techniques, which aim to enhance a smartphone’s performance through utilizing powerful cloud servers, were suggested. Among such techniques, execution offloading, which migrates a thread between a mobile device and a server, is often employed. In such execution offloading techniques, it is typical to dynamically decide what code part is to be offloaded through decision making algorithms. In order to achieve optimal offloading performance, however, the gain and cost of offloading must be predicted accurately for such algorithms. Previous works did not try hard to do this because it is usually expensive to make an accurate prediction. Thus in this paper, we introduce novel techniques to automatically generate accurate and efficient method-wise performance predictors for mobile applications and empirically show they enhance the performance of offloading.     

Optimizing Grid-Based Workflow Execution

Large-scale applications can be expressed as a set of tasks with data dependencies between them, also known as application workflows. Due to the scale and data processing requirements of these applications, they require Grid computing and storage resources. So far, the focus has been on developing easy to use interfaces for composing these workflows and finding an optimal mapping of tasks in the workflow to the Grid resources in order to minimize the completion time of the application. After this mapping is done, a workflow execution engine is required to run the workflow over the mapped resources. In this paper, we show that the performance of the workflow execution engine in executing the workflow can also be a critical factor in determining the workflow completion time. Using Condor as the workflow execution engine, we examine the various factors that affect the completion time of a fine granularity astronomy workflow. We show that changing the system parameters that influence these factors and restructuring the workflow can drastically reduce the completion time of this class of workflows. We also examine the effect on the optimizations developed for the astronomy application on a coarser granularity biology application. We were able to reduce the completion time of the Montage and the Tomography application workflows by 90% and 50%, respectively.     

Grid Service Orchestration Using the Business Process Execution Language (BPEL)

Modern scientific applications often need to be distributed across Grids. Increasingly applications rely on services, such as job submission, data transfer or data portal services. We refer to such services as Grid services. While the invocation of Grid services could be hard coded in theory, scientific users want to orchestrate service invocations more flexibly. In enterprise applications, the orchestration of web services is achieved using emerging orchestration standards, most notably the Business Process Execution Language (BPEL). We describe our experience in orchestrating scientific workflows using BPEL. We have gained this experience during an extensive case study that orchestrates Grid services for the automation of a polymorph prediction application. Using this example, we explain the extent with which the BPEL language supports the definition of scientific workflows. We then describe the reliability, performance and scalability that can be achieved by executing a complex scientific workflow with ActiveBPEL, an industrial strength but freely available BPEL engine. *The work has been funded by the UK EPSRC through grants GR/R97207/01 (e-Materials) and GR/S90843/01 (OMII Managed Programme).     

基于移动代理的分布式入侵检测系统的研究

分析了现行的移动代理入侵检测系统的缺点,在此基础上,针对性地提出了一种基于移动Agent的分布式入侵检测系统模型MADIDS(mobile agent-based distributed intrusion detection system).该模型为每一个移动代理添加了独立的ID,并加入身份验证、完整性鉴定和加密机制.通过多Agent技术来实现检测自治化和多主机间检测信息的协调,提高了入侵检测系统自身的安全性,有效地检测了分布式的攻击行为.实验测试结果表明了其良好的性能.     

Network-aware support for mobile distributed teams

An experiment evaluated network-aware support to increase understanding of the factors that are important for successful teamwork in mobile geographically dispersed teams of first responders. Participants performed a simulated search and rescue team task and were equipped with a digitized map and real-time situation updates on the location of other participants in a simulated disaster area. The connection to a server, however, was made deliberately error-prone, leading to occasional losses of network connections. Consequently, participants were not provided with real-time situation updates. To deal with this problem we equipped team members with a network-aware application that signaled network loss to them and adapted the graphical representation of the location of fellow team members accordingly to the quality of location information present. The experiment revealed that presenting complete and reliable geospatial information improves teamwork. Teams connected to a server over a fast and reliable link showed superior performance over teams with no network connection whatsoever to a server. The present study failed, however, to demonstrate the added value of network-aware support when teams had to collaborate in the presence of an unreliable communications infrastructure. Although participants indicated a slight preference for the network-aware application over a condition without support signaling network loss, no differences were observed in team process and outcome measures.     

A framework for adaptive execution in grids

Grids offer a dramatic increase in the number of available processing and storing resources that can be delivered to applications. However, efficient job submission and management continue being far from accessible to ordinary scientists and engineers due to their dynamic and complex nature. This paper describes a new Globus based framework that allows an easier and more efficient execution of jobs in a ‘submit and forget’ fashion. The framework automatically performs the steps involved in job submission and also watches over its efficient execution. In order to obtain a reasonable degree of performance, job execution is adapted to dynamic resource conditions and application demands. Adaptation is achieved by supporting automatic application migration following performance degradation, ‘better’ resource discovery, requirement change, owner decision or remote resource failure. The framework is currently functional on any Grid testbed based on Globus because it does not require new system software to be installed in the resources. The paper also includes practical experiences of the behavior of our framework on the TRGP and UCM‐CAB testbeds. Copyright © 2004 John Wiley & Sons, Ltd.     

A timed mobile agent planning approach for distributed information retrieval in dynamic network environments

The number of mobile agents and total execution time are two factors used to represent the system overhead that must be considered as part of mobile agent planning (MAP) for distributed information retrieval. In addition to these two factors, the time constraints at the nodes of an information repository must also be taken into account when attempting to improve the quality of information retrieval. In previous studies, MAP approaches could not consider dynamic network conditions, e.g., variable network bandwidth and disconnection, such as are found in peer-to-peer (P2P) computing. For better performance, mobile agents that are more sensitive to network conditions must be used. In this paper, we propose a new MAP approach that we have named Timed Mobile Agent Planning (Tmap). The proposed approach minimizes the number of mobile agents and total execution time while keeping the turnaround time to a minimum, even if some nodes have a time constraint. It also considers dynamic network conditions to reflect the dynamic network condition more accurately. Moreover, we incorporate a security and fault-tolerance mechanism into the planning approach to better adapt it to real network environments.     

A trustworthy agent-based encrypted access control method for mobile cloud computing environment

To strengthen the security of access control protocols for mobile cloud environment, dynamic attributes of mobile devices are used. The weak or disconnection issue of the mobile network is a critical task to deal with. The proposed approach provides access control as well as data confidentiality using dynamic attributes encryption. The pairs of mobile agents are used to deal with the issue of network connection. The secret key is distributed using the anonymous key-issuing protocol which preserves the anonymity of the user. The approach is implemented in a real mobile cloud environment, and the performance under various parameters is evaluated.     

Deploying personalized mobile services in an agent-based environment

The mobile Internet allows users to obtain digitized contents and services from wired and wireless networks virtually anywhere at any time via different handheld mobile devices. However, due to the distinct features of mobile users, mobile devices and wireless networks, deploying mobile services is not as straightforward as generally expected. To ensure the success of mobile services, this paper presents a multi-agent framework that considers different contexts to support personalized services on wireless networks. In the proposed approach, client users, content providers, and service providers are all considered as software agents. They interoperate on the same platform to request and deliver mobile services. The most important issues related to agent operations and context awareness in an agent world are also discussed and analyzed. To verify our framework, different application services are developed accordingly on a publicly available middleware platform. Experiments are conducted for both services to evaluate their corresponding performance. The preliminary results show that our multi-agent approach to personalization is promising and efficient in the deployment of mobile services.     

Control of group of mobile autonomous agents via local strategies

This paper considers the formation control problem of multi-agent systems in a distributed fashion. Two cases of the information propagating topologies among multiple agents, characterized by graphics model, are considered. One is fixed topology. The other is switching topology which represents the limited and less reliable information exchange. The local formation control strategies established in this paper are based on a simple modification of the existing consensus control strategies. Moreover, some existing convergence conditions are shown to be a special case of our model even in the continuous-time consensus case. Therefore, the results of this paper extend the existing results about the consensus problem.     

Algorithms for validating E-tickets in mobile computing environment

E-tickets issued online can be used by different vendors to provide services such as discount coupons for E-shopping, or an entrance for a football game. One major issue associated with E-tickets is the problem of validation, which becomes more severe in a mobile environment due to mobility of a mobile host (MH) and frequent failure/disconnection of validation servers known as mobile support stations (MSSs). Some additional problems include the identification of duplicate submissions of an E-ticket by a MH. Thus, this paper proposes two protocols using the Flat and Hierarchical schemes for E-ticket processing and validation in a mobile environment that guarantee at least and at most once property (each E-ticket is validated at least and at most once). The protocols have been validated and compared through complexity analysis and experiments.     

Multi-objective list scheduling of workflow applications in distributed computing infrastructures

Executing large-scale applications in distributed computing infrastructures (DCI), for example modern Cloud environments, involves optimization of several conflicting objectives such as makespan, reliability, energy, or economic cost. Despite this trend, scheduling in heterogeneous DCIs has been traditionally approached as a single or bi-criteria optimization problem. In this paper, we propose a generic multi-objective optimization framework supported by a list scheduling heuristic for scientific workflows in heterogeneous DCIs. The algorithm approximates the optimal solution by considering user-specified constraints on objectives in a dual strategy: maximizing the distance to the user’s constraints for dominant solutions and minimizing it otherwise. We instantiate the framework and algorithm for a four-objective case study comprising makespan, economic cost, energy consumption, and reliability as optimization goals. We implemented our method as part of the ASKALON environment (Fahringer et al., 2007) for Grid and Cloud computing and demonstrate through extensive real and synthetic simulation experiments that our algorithm outperforms related bi-criteria heuristics while meeting the user constraints most of the time.     

DAG分割模型下的云工作流调度策略

为了优化云工作流调度的经济代价和执行效率,提出一种基于有向无循环图（DAG）分割的工作流调度算法PBWS。以工作流调度效率与代价同步优化为目标,算法将调度求解过程划分为三个阶段进行：工作流DAG结构分割、分割结构调整及资源分配。工作流DAG结构分割阶段在确保任务间执行顺序依赖的同时求解初始的任务分割图;分割结构调整阶段以降低执行跨度为目标,在不同分割间对任务进行重分配;资源分配阶段旨在选择代价最高效的任务与资源映射关系,确保资源的总空闲时间最小。利用五种科学工作流DAG模型对算法进行了仿真实验。结果表明。PBWS算法仅以较小的执行跨度为开销,极大降低了工作流执行代价,实现了调度效率与调度代价的同步优化,其综合性能是优于同类型算法的。     

Improvement of group performance of job distributed mobile robots by an emotionally biased control system

This paper deals with the implementation of emotions in mobile robots performing a specified task in a group in order to develop intelligent behavior and easier forms of communication. The overall group performance depends on the individual performance, group communication, and the synchronization of cooperation. With their emotional capability, each robot can distinguish the changed environment, can understand a colleague robot’s state, and can adapt and react with a changed world. The adaptive behavior of a robot is derived from the dominating emotion in an intelligent manner. In our control architecture, emotion plays a role to select the control precedence among alternatives such as behavior modes, cooperation plans, and goals. Emotional interaction happens among the robots, and a robot is biased by the emotional state of a colleague robot in performing a task. Here, emotional control is used for a better understanding of the colleague’s internal state, for faster communication, and for better performance eliminating dead time. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

移动边缘环境下面向工作流管理的计算迁移方法

针对移动边缘环境下移动设备大量的能源消耗问题，为了优化移动设备的能源消耗，提出一种能耗感知的工作流计算迁移（EOW）方法。首先，基于排队论分析边缘设备中计算任务的平均等待时间，建立了移动设备的时间模型和能耗模型；然后，基于非支配排序算法（NSGA-Ⅲ）提出对应的计算迁移方法，对工作流的计算任务进行合理的分配，将一部分计算任务留在移动设备处理，或者迁移到边缘计算平台和远程云端，实现每个移动设备的节能目标；最后，通过CloudSim仿真平台对提出的计算迁移方法进行仿真和对比实验。实验结果表明，EOW方法能够明显地减少每个移动设备的能源消耗，同时满足每一个工作流的截止时间的要求。     

SHadoop: Improving MapReduce performance by optimizing job execution mechanism in Hadoop clusters

As a widely-used parallel computing framework for big data processing today, the Hadoop MapReduce framework puts more emphasis on high-throughput of data than on low-latency of job execution. However, today more and more big data applications developed with MapReduce require quick response time. As a result, improving the performance of MapReduce jobs, especially for short jobs, is of great significance in practice and has attracted more and more attentions from both academia and industry. A lot of efforts have been made to improve the performance of Hadoop from job scheduling or job parameter optimization level. In this paper, we explore an approach to improve the performance of the Hadoop MapReduce framework by optimizing the job and task execution mechanism. First of all, by analyzing the job and task execution mechanism in MapReduce framework we reveal two critical limitations to job execution performance. Then we propose two major optimizations to the MapReduce job and task execution mechanisms: first, we optimize the setup and cleanup tasks of a MapReduce job to reduce the time cost during the initialization and termination stages of the job; second, instead of adopting the loose heartbeat-based communication mechanism to transmit all messages between the JobTracker and TaskTrackers, we introduce an instant messaging communication mechanism for accelerating performance-sensitive task scheduling and execution. Finally, we implement SHadoop, an optimized and fully compatible version of Hadoop that aims at shortening the execution time cost of MapReduce jobs, especially for short jobs. Experimental results show that compared to the standard Hadoop, SHadoop can achieve stable performance improvement by around 25% on average for comprehensive benchmarks without losing scalability and speedup. Our optimization work has passed a production-level test in Intel and has been integrated into the Intel Distributed Hadoop (IDH). To the best of our knowledge, this work is the first effort that explores on optimizing the execution mechanism inside map/reduce tasks of a job. The advantage is that it can complement job scheduling optimizations to further improve the job execution performance.     

A distributed motion coordination strategy for multiple nonholonomic mobile robots in cooperative hunting operations

This paper presents a distributed smooth time-varying feedback control law for coordinating motions of multiple nonholonomic mobile robots of the Hilare-type to capture/enclose a target by making troop formations. This motion coordination is a cooperative behavior for security against invaders in surveillance areas. Each robot in this control law has its own coordinate system and it senses a target/invader, other robots and obstacles, to achieve this cooperative behavior without making any collision. Each robot especially has a two-dimensional control input referred to as a “formation vector” and the formation is controllable by the vectors. The validity of this control law is supported by computer simulations.