Resource location is a necessary operation for computer applications. In large scale peer-to-peer systems, random search is a scalable approach for locating dynamic resources. Current peer-to-peer systems can be partitioned into those which rely upon the Internet for message routing and those which utilize an overlay network. These two approaches result in different connectivity topologies. This thesis analyzes the effect of topological differences on the effectiveness of random search. After demonstrating the benefits of an overlay network, we propose a hybrid approach for resource location. Our proposed protocol provides deterministic searching capabilities which can help prevent request failures for sensitive applications.

Resource location is a necessary operation for computer applications. In large scale peer-to-peer systems, random search is a scalable approach for locating dynamic resources. Current peer-to-peer systems can be partitioned into those which rely upon the Internet for message routing and those which utilize an overlay network. These two approaches result in different connectivity topologies. This thesis analyzes the effect of topological differences on the effectiveness of random search. After demonstrating the benefits of an overlay network, we propose a hybrid approach for resource location. Our proposed protocol provides deterministic searching capabilities which can help prevent request failures for sensitive applications.

Service discovery is a driving force in realizing pervasive computing. It provides a way for users and services to locate and interact with other services in a pervasive computing environment. Unfortunately, current service discovery solutions do not capture the effects of the human or physical world and do not deal well with diverse device populations; both of which are characteristics of pervasive computing environments. This research concentrates on the examination and fulfillment of the goals of two of the four components of service discovery, service description and dissemination. It begins with a review of and commentary on current service discovery solutions. Following this review, is the formulation of the problem statement, including a full explanation of the problems mentioned above. The problem formulation is followed by an explanation of the process followed to design and build solutions to these problems. These solutions include the Pervasive Service Description Language (PSDL), the Pervasive Service Query Language (PSQL), and the Multi-Assurance Delivery Protocol (MADEP). Prototype implementations of the components are used to validate feasibility and evaluate performance. Experimental results are presented and analyzed. This work concludes with a discussion of overall conclusions, directions for future work, and a list of contributions. / Ph. D.

Labor mobility in the rural area of Mainland China plays recently an important role in its economic development process. And this enormous and inexpensive labor attracts foreign investments, including Taiwanese investment, to enter Mainland China¡¦s market, and, further, drives economic development of Asia-Pacific Region. However, from the viewpoint of Rural-Urban Dualism theory, on the social level, rural labors can not take part in political life, and preserve their rights. Thus, they become ¡§Silent Class¡¨ in the Chinese urban society. On the economic level, serious public security problems derivative from labor disputes and conflicts, and it attracts highly concerns of Central of Chinese Communist Party (CCP), and issues ¡§Constructing Harmonious Community and Well-Off Society¡¨; and on the social level, continued expanding poverty gap, social rejection, and prejudice cause deep impact on those labors. This studying focus on the changing steps of supply and demand of rural labor, in order to discuss the developmental trend of transferring process of rural labor form past to present, even to the future. Therefore, this essay concentrates on the changing mobility of rural labor in some aspects, for example regions, identifications, careers, and life forms, and political, social economic, cultural, policy/urbanization, and market/occupation connections between rural and urban area. The Result of studying is, Central of CCP has 3 ways to solve problems beneath the surface of rural labor and urbanization: 1. Accelerating transferring process of rural surplus labor with economic development strategy; 2. Upgrading skill standard of rural labor, to guarantee employment; 3. Promoting and enlarging domestic consume, to constrain inflation. At the same time, the capability of labor unions should be reinforced and the organized degree of rural labor should be improved. Hoping that, they are able to play a more active role to protect rights of rural labors.

<p>Network and system management has always been of concern for telecommunication and computer system operators. The need for standardization was recognised already 20 years ago, hence several standards for network management exist today. However, the ever-increasing number of units connected to networks and the ever-increasing number of services being provided results in significant increased complexity of average network environments. This challenges current management systems. In addition to the general increase in complexity the trend among network owners and operators of merging several single service networks into larger, heterogeneous and complex full service networks challenges current management systems even further. The full service networks will require management systems more powerful than what is possible to realize basing systems purely on todays management standards. This thesis presents a distributed stochastic optimization algorithm which enables implementations of highly robust and efficient management tools. These tools may be integrated into management systems and potentially make the systems more powerful and better prepared for management of full service networks.</p><p>Emergent behavior is common in nature and easily observable in colonies of social insects and animals. Even an old oak tree can be viewed as an emergent system with its collection of interacting cells. Characteristic for any emergent system is how the overall behavior of the system emerge from many relatively simple, restricted behaviors interacting, e.g. a thousand ants building a trail, a flock of birds flying south or millions of cells making a tree grow. No centralized control exist, i.e. no single unit is in charge making global decisions. Despite distributed control, high work redundancy and stochastic behavior components, emergent systems tend to be very efficient problem solvers. In fact emergent systems tend to be both efficient, adaptive and robust which are three properties indeed desirable for a network management system. The algorithm presented in this thesis relates to a class of emergent behavior based systems known as swarm intelligence systems, i.e. the algorithm is potentially efficient, adaptive and robust.</p><p>On the contrary to other related swarm intelligence algorithms, the algorithm presented has a thorough formal foundation. This enables a better understanding of the algorithm’s potentials and limitations, and hence enables better adaptation of the algorithm to new problem areas without loss of efficiency, adaptability or robustness. The formal foundations are based on work by Reuven Rubinstein on cross entropy driven optimization. The transition from Ruinstein’s centralized and synchronous algorithm to a distributed and asynchronous algorithm is described, and the distributed algorithm’s ability to solve complex problems (NP-complete) efficiently is demonstrated.</p><p>Four examples of how the distributed algorithm may be applied in a network management context are presented. A system for finding near optimal patterns of primary/backup paths together with a system for finding cyclic protection paths in mesh networks demonstrate the algorithm’s ability to act as a tool helping management system to ensure quality of service. The algorithm’s potential as a management policy implementation mechanism is also demonstrated. The algorithm’s adaptability is shown to enable resolution of policy conflicts in a soft manner causing as little loss as possible. Finally, the algorithm’s ability to find near optimal paths (i.e. sequences) of resources in networks of large scale is demonstrated.</p>

Network and system management has always been of concern for telecommunication and computer system operators. The need for standardization was recognised already 20 years ago, hence several standards for network management exist today. However, the ever-increasing number of units connected to networks and the ever-increasing number of services being provided results in significant increased complexity of average network environments. This challenges current management systems. In addition to the general increase in complexity the trend among network owners and operators of merging several single service networks into larger, heterogeneous and complex full service networks challenges current management systems even further. The full service networks will require management systems more powerful than what is possible to realize basing systems purely on todays management standards. This thesis presents a distributed stochastic optimization algorithm which enables implementations of highly robust and efficient management tools. These tools may be integrated into management systems and potentially make the systems more powerful and better prepared for management of full service networks. Emergent behavior is common in nature and easily observable in colonies of social insects and animals. Even an old oak tree can be viewed as an emergent system with its collection of interacting cells. Characteristic for any emergent system is how the overall behavior of the system emerge from many relatively simple, restricted behaviors interacting, e.g. a thousand ants building a trail, a flock of birds flying south or millions of cells making a tree grow. No centralized control exist, i.e. no single unit is in charge making global decisions. Despite distributed control, high work redundancy and stochastic behavior components, emergent systems tend to be very efficient problem solvers. In fact emergent systems tend to be both efficient, adaptive and robust which are three properties indeed desirable for a network management system. The algorithm presented in this thesis relates to a class of emergent behavior based systems known as swarm intelligence systems, i.e. the algorithm is potentially efficient, adaptive and robust. On the contrary to other related swarm intelligence algorithms, the algorithm presented has a thorough formal foundation. This enables a better understanding of the algorithm’s potentials and limitations, and hence enables better adaptation of the algorithm to new problem areas without loss of efficiency, adaptability or robustness. The formal foundations are based on work by Reuven Rubinstein on cross entropy driven optimization. The transition from Ruinstein’s centralized and synchronous algorithm to a distributed and asynchronous algorithm is described, and the distributed algorithm’s ability to solve complex problems (NP-complete) efficiently is demonstrated. Four examples of how the distributed algorithm may be applied in a network management context are presented. A system for finding near optimal patterns of primary/backup paths together with a system for finding cyclic protection paths in mesh networks demonstrate the algorithm’s ability to act as a tool helping management system to ensure quality of service. The algorithm’s potential as a management policy implementation mechanism is also demonstrated. The algorithm’s adaptability is shown to enable resolution of policy conflicts in a soft manner causing as little loss as possible. Finally, the algorithm’s ability to find near optimal paths (i.e. sequences) of resources in networks of large scale is demonstrated.