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Network tomography allows the measurements of end-to-end to infer network internal links characteristics such as packet loss rates and delay. In this work, we apply concepts from compressed sensing and Maximum A-Posteriori (MAP) estimation to the delay estimation problem. We propose a new delay tomography scheme which can be considered as a variation of l 1 -l 2 optimization. The proposed scheme assumes the link delay is exponential which goes further than just considering sparsity of it in former works. We also consider the clock synchronization error between source and receiver in path delay measurement, which we treat as additive Gaussian random variables. We conduct a simulation performance analysis of delay estimation and congestion detection, demonstrating that higher estimation accuracy can be obtained through the proposed scheme.

To solve job-shop production scheduling problem, we presented a new hybrid optimum arithmetic of using genetic algorithm and MAS(multi-agent system) composite-spring-net. Introduced the structure and model of genetic algorithm, illuminated the basic principle of spring-net arithmetic. By the experiment proving, the hybrid application of GA and sping-net arithmetic can make favorable effect on solving the problems of job-shop schedule.

With the developments of related techniques in telecommunication and computer sciences, wireless sensor networks have been used more and more widely. While sensor nodes in wireless sensor networks have very limited memory spaces and power. In this paper, we propose a new method to preprocess the query predicates. The size of the relational table can be further reduced using the aggregated query predicates. The reduced relational table can be stored on the sensor nodes. This may cause false positive but definitely no false negative. When the required data are sent back to the sink, we can do join operation between the real query predicate and the relational table again, and eliminate the redundant data.

In this paper, we discuss the design and implementation of a mobile object management system that makes use of the existing GSM (Global System for Mobile Communication) networks and it's extension- GPRS(General Packet Radio Service) for data communication. We use a novel Composite Communication Scheme (CCS), which uses SMS (Short Message Service) and GPRS to achieve reliable and economical communication between mobile objects and the control center. We also use Unified Data Management (UDM) for control center management, which significantly reduces the cost of maintaining separate data centers. We have deployed our services in two medium-sized cities with real users. The cost evaluation shows the high performance, usability and cost-effectiveness of this service in real production environment.