Categorization of risk factors for distributed agile projects

ContextOrganizations combine agile approach and Distributed Software Development (DSD) in order to develop better quality software solutions in lesser time and cost. It helps to reap the benefits of both agile and distributed development but pose significant challenges and risks. Relatively scanty evidence of research on the risks prevailing in distributed agile development (DAD) has motivated this study.ObjectiveThis paper aims at creating a comprehensive set of risk factors that affect the performance of distributed agile development projects and identifies the risk management methods which are frequently used in practice for controlling those risks.MethodThe study is an exploration of practitioners’ experience using constant comparison method for analyzing in-depth interviews of thirteen practitioners and work documents of twenty-eight projects from thirteen different information technology (IT) organizations. The field experience was supported by extensive research literature on risk management in traditional, agile and distributed development.ResultsAnalysis of qualitative data from interviews and project work documents resulted into categorization of forty-five DAD risk factors grouped under five core risk categories. The risk categories were mapped to Leavitt’s model of organizational change for facilitating the implementation of results in real world. The risk factors could be attributed to the conflicting properties of DSD and agile development. Besides that, some new risk factors have been experienced by practitioners and need further exploration as their understanding will help the practitioners to act on time.ConclusionOrganizations are adopting DAD for developing solutions that caters to the changing business needs, while utilizing the global talent. Conflicting properties of DSD and agile approach pose several risks for DAD. This study gives a comprehensive categorization of the risks faced by the practitioners in managing DAD projects and presents frequently used methods to reduce their impact. The work fills the yawning research void in this field.     

EV-DO监测系统中R-P接口业务信令追踪的研究与实现

在EV-DO网络中,信令监测系统对于用户数据业务运营的分析尤为重要。针对EV-DO网络中的重要数据接口R-P接口间A11及PPP信令CDR(Call Data Record)的合成,结合主叫和寻呼过程的业务特征,提出一系列优化及改进方案。经过EV-DO现网数据的测试以及产生的相应实验结果表明,优化信令与业务数据消息间的关联机制,缩短了数据网络寻呼与用户主叫业务信令的追踪统计时间最高可达30 s,指标的细化提升了故障定位准确性。这项改进方案对于优化网络运维的分析平台有着重要意义。     

基于区域扩散机制的无线传感器网络时间同步算法

针对当前无线传感器网络时间同步算法无法满足物联网对于网络实时性的要求,提出了一种基于区域扩散的无线传感器网络时间同步算法。该算法分为两个阶段进行:第一阶段根据生物觅食理论(OFT),按照收益率最高的原理提出一种代言人信息选择算法(SIE)进行区域内时间同步;第二阶段根据时间偏移量最小节点选择区域代言人并在区域之间进行二次同步,同时将同步过程映射到马尔可夫链,提出基于马尔可夫链的代言人加速算法(MarSAA)。理论分析和实验证明,提出的算法具有较好的时间复杂性;并且两阶段算法可以并行进行,相对于传统算法在全网时间同步上具有非常好的性能。     

基于改进粒子群算法的多目标分布式电源选址定容规划

通过分析分布式电源对配电网的影响,以有功功率损耗、电压质量及分布式电源总容量为优化目标,基于模糊理论建立了分布式电源在配电网中选址定容的多目标优化模型,并提出了一种改进粒子群算法进行求解。在算例仿真中,基于IEEE 14标准节点系统,采用MATLAB仿真工具对所提算法进行了测试,证实了所提算法全局搜索能力较强、收敛速度较快,并通过比较分析验证了该模型和算法的可行性及有效性。     

遥感网格的数据压缩与任务分配方法研究

网格计算作为分布式计算在科学计算领域的发展方向,可以为对地观测数据的处理提供强大的计算力。在分析遥感信息服务网格节点(Remote Sensing Information Service Grid Nodes,RSSN)中网络数据传输和负载均衡两个关键问题的基础上,提出了一种有效的基于游程编码和Huffman编码的数据压缩方法和基于"计算端元"的任务分配策略,该方法针对遥感影像特点进行有效数据压缩,具有较好的压缩比,达到了17%,且能实现任务负载均衡。并在遥感信息服务网格节点计算平台上,以中国范围内1km分辨率气溶胶光学厚度(Aerosol Optical Depth,AOD)反演计算为例,从压缩率和计算时间效率方面验证和分析了上述方法的有效性。     

Chaotic bat swarm optimisation (CBSO)

Bat swarm optimisation (BSO) is a novel heuristic optimisation algorithm that is being used for solving different global optimisation problems. The paramount problem in BSO is that it severely suffers from premature convergence problem, that is, BSO is easily trapped in local optima. In this paper, chaotic-based strategies are incorporated into BSO to mitigate this problem. Ergodicity and non-repetitious nature of chaotic functions can diversify the bats and mitigate premature convergence problem. Eleven different chaotic map functions along with various chaotic BSO strategies are investigated experimentally and the best one is chosen as the suitable chaotic strategy for BSO. The results of applying the proposed chaotic BSO to different benchmark functions vividly show that premature convergence problem has been mitigated efficiently. Actually, chaotic-based BSO significantly outperforms conventional BSO, cuckoo search optimisation (CSO), big bang-big crunch algorithm (BBBC), gravitational search algorithm (GSA) and genetic algorithm (GA).     

基于软构件的Web办公系统的设计与实现

该文对软构件进行了研究,提出了利用DSCIE（Distributed Software Component Integrated Environment）,即分布式软构件集成环境的框架开发Web办公系统的方法。Web办公系统通过.net技术来实现。并且基于这个框架成功开发出了铁路Web办公系统。     

非结构化数据存储管理研究

非结构化数据通常指相对于关系数据而言没有固定的显式结构的数据,比如视频、音频、图像、文档等非结构化数据。根据权威数据咨询机构或研究机构的预测报告显示,近 5～10年的数据量将呈指数级增长,而其中的非结构化数据占到当前数字信息总量的70%～85%。面对如此庞大的数据量和信息量,如何有效管理非结构化数据、获得有价值的信息或知识显得迫在眉睫。(非结构化) 数据管理可以简单化为3个目标,即:实现数据的“存得下、管得了、用的上”。本文将主要围绕前两个基本目标介绍目前的非结构化数据存储管理的研究情况。同时介绍中国人民大学非结构数据管理(Unstructured DataManagement,UDM)研究小组基于“自由表”数据模型和BUD(Bank of Unstructured Data)参考体系模型在这一个问题上所作的初步研究与探索工作,以及在原型平台myBUD中的若干存储管理技术。     

A distributed collaborative product design environment based on semantic norm model and role-based access control

With the boom of Internet Technology, it becomes possible to combine designers from different disciplines into one team to support product design globally. In this paper, a distributed collaborative product design environment is presented to support top-down process oriented product design. In conceptual design stage, the artifact is managed by semantic norm model (SNM). In SNM, the designers can define virtual components at early design stage and instantiate those components at later detailed design stage. By role-based access control (RBAC), different roles with corresponding permissions could be assigned to distributed designers, and the designers could concurrently modify different components of the product relevant to his or her roles. Based on the SNM and RBAC system, a distributed collaborative product design environment is developed and the top-down oriented product design process is demonstrated.