Transformational approaches to generating design and implementation models from requirements can bring effectiveness and quality to software development. In this paper we present a framework and associated techniques to generate the process model of a service composition from a set of temporal business rules. Dedicated techniques including path-finding, branching structure identification and parallel structure identification are used for semi-automatically synthesizing the process model from the semantics-equivalent Finite State Automata of the rules. These process models naturally satisfy the prescribed behavioral constraints of the rules. With the domain knowledge encoded in the temporal business rules, an executable service composition program, e.g., a BPEL program, can be further generated from the process models. A running example in the e-business domain is used for illustrating our approach throughout this paper.

Reflective middleware opens up the implementation details of middleware platform and applications at runtime for improving the adaptability of middleware-based systems. However, such openness brings new challenges to access control of the middleware-based systems. Some users can access the system via reflective entities, which sometimes cannot be protected by access control mechanisms of traditional middleware. To deliver high adaptability securely, reflective middleware should be equipped with proper access control mechanisms for potential access control holes induced by reflection. One reason of integrating these mechanisms in reflective middleware is that one goal of reflective middleware is to equip applications with reflection capabilities as transparent as possible. This paper studies how to design a reflective J2EE middleware --- PKUAS with access control in mind. At first, a computation model of reflective system is built to identify all possible access control points induced by reflection. Then a set of access control mechanisms, including the wrapper of MBeans and a hierarchy of Java class loaders, are equipped for controlling the identified access control points. These mechanisms together with J2EE access control mechanism form the access control framework for PKUAS. The paper evaluates the security and the performance overheads of the framework in quality and quantity.

Our study introduces a novel distributed query plan refinement phase in an enhanced architecture of distributed query processing engine (DQPE). Query plan refinement generates potentially efficient distributed query plan by reusable aggregate query shipping (RAQS) approach. The approach improves response time at the cost of pre-processing time. If the overheads could not be compensated by query results reusage, RAQS is no more favorable. Therefore a global cost estimation model is employed to get proper operators: RR\_Agg, R\_Agg, or R\_Scan. For the purpose of reusing results of queries with aggregate function in distributed query processing, a multi-level hybrid view caching (HVC) scheme is introduced. The scheme retains the advantages of partial match and aggregate query results caching. By our solution, evaluations with distributed TPC-H queries show significant improvement on average response time.

Vehicular networks have attracted extensive attention in recent years for their promises in improving safety and enabling other value-added services. Most previous work focuses on designing the media access and physical layer protocols. Privacy issues in vehicular systems have not been well addressed. We argue that privacy is a {\it user-specific} concept, and a good privacy protection mechanism should allow users to select the levels of privacy they wish to have. To address this requirement, we propose an adaptive anonymous authentication mechanism that can trade off the anonymity level with computational and communication overheads (resource usage). This mechanism, to our knowledge, is the first effort on adaptive anonymous authentication. The resources used by our protocol are few. A high traffic volume of 2000 vehicles per hour consumes about 60kbps bandwidth, which is less than one percent of the bandwidth of DSRC (Dedicated Short Range Communications). By using adaptive anonymity, the protocol response time can further be improved 2$\sim$4 times with less than 20\% bandwidth overheads.

We describe an effective resource location framework for ubiquitous computing environments populated by a diverse set of networks, devices, services and computational entities. Our framework provides context adaptation with the aid of a middleware service to improve the quality of resource location. A resource location protocol suitable to each type of network locates resource effectively by means of dynamic reconfiguration to the current context. Our framework is also refined by support for interoperability between different types of resource location protocols occurring across a hybrid ubiquitous network. These characteristics also reduce the control overhead for resource location, saving resource, decreasing latency and permitting a considerable degree of scalability.

Routing is a fundamental problem in wireless sensor networks. Most previous routing protocols are challenged when used in large dynamic networks as they suffer from either poor scalability or the void problem. In this paper, we propose a new geographic routing protocol, SBFR (Scoped Bellman-Ford Routing), for large dynamic wireless sensor networks. The basic idea is that each node keeps a view scope of the network by computing distance vectors using the distributed Bellman-Ford method, and maintains a cost for routing to the sink. When forwarding a packet, a node picks the node with minimum cost in its routing table as a temporary landmark. While achieving good scalability, it also solves the void problem in an efficient manner through the combination of Bellman-Ford routing and cost-based geographic routing. Analytical and simulation results show that SBFR outperforms other routing protocols not only because of its robustness and scalability but also its practicality and simplicity.

Sensor networks are widely used in many applications to collaboratively collect information from the physical environment. In these applications, the exploration of the relationship and linkage of sensing data within multiple regions can be naturally expressed by joining tuples in these regions. However, the highly distributed and resource-constraint nature of the network makes join a challenging query. In this paper, we address the problem of processing join query among different regions progressively and energy-efficiently in sensor networks. The proposed algorithm PEJA (Progressive Energy-efficient Join Algorithm) adopts an {\it event-driven} strategy to output the joining results as soon as possible, and alleviates the storage shortage problem in the in-network nodes. It also installs {\it filters} in the joining regions to prune unmatchable tuples in the early processing phase, saving lots of unnecessary transmissions. Extensive experiments on both synthetic and real world data sets indicate that the PEJA scheme outperforms other join algorithms, and it is effective in reducing the number of transmissions and the delay of query results during the join processing.

Detecting duplicates in data streams is an important problem that has a wide range of applications. In general, precisely detecting duplicates in an unbounded data stream is not feasible in most streaming scenarios, and, on the other hand, the elements in data streams are always time sensitive. These make it particular significant approximately detecting duplicates among newly arrived elements of a data stream within a fixed time frame. In this paper, we present a novel data structure, Decaying Bloom Filter (DBF), as an extension of the Counting Bloom Filter, that effectively removes stale elements as new elements continuously arrive over sliding windows. On the DBF basis we present an efficient algorithm to approximately detect duplicates over sliding windows. Our algorithm may produce false positive errors, but not false negative errors as in many previous results. We analyze the time complexity and detection accuracy, and give a tight upper bound of false positive rate. For a given space $G$ bits and sliding window size $W$, our algorithm has an amortized time complexity of $O(\sqrt{G/W})$. Both analytical and experimental results on synthetic data demonstrate that our algorithm is superior in both execution time and detection accuracy to the previous results.

Secure XML query answering to protect data privacy and semantic cache to speed up XML query answering are two hot spots in current research areas of XML database systems. While both issues are explored respectively in depth, they have not been studied together, that is, the problem of semantic cache for secure XML query answering has not been addressed yet. In this paper, we present an interesting joint of these two aspects and propose an efficient framework of semantic cache for secure XML query answering, which can improve the performance of XML database systems under secure circumstances. Our framework combines access control, user privilege management over XML data and the state-of-the-art semantic XML query cache techniques, to ensure that data are presented only to authorized users in an efficient way. To the best of our knowledge, the approach we propose here is among the first beneficial efforts in a novel perspective of combining caching and security for XML database to improve system performance. The efficiency of our framework is verified by comprehensive experiments.

In recent years, management of moving objects has emerged as an active topic of spatial access methods. Various data structures (indexes) have been proposed to handle queries of moving points, for example, the well-known B$^x$-tree uses a novel mapping mechanism to reduce the index update costs. However, almost all the existing indexes for predictive queries are not applicable in certain circumstances when the update frequencies of moving objects become highly variable and when the system needs to balance the performance of updates and queries. In this paper, we introduce two kinds of novel indexes, named B$^y$-tree and $\al {\rm B}^y$-tree. By associating a {\em prediction life period} with every moving object, the proposed indexes are applicable in the environments with highly variable update frequencies. In addition, the $\al {\rm B}^y$-tree can balance the performance of updates and queries depending on a balance parameter. Experimental results show that the B$^y$-tree and $\al {\rm B}^y$-tree outperform the B$^x$-tree in various conditions.

When a 3D model is transmitted over a lossy network, some model information may inevitably be missing. Under such situation, one may not be able to visualize the receiving model unless the lost model information has been retransmitted. Progressive model transmission offers an alternative to avoid the ``all or nothing situation'' by allowing a model to be visualized with a degraded quality when only part of the model data has been received. Unfortunately, in case some model refinement information is missing, one may still need to wait for such information to be retransmitted before the model can be rendered with a desired visual quality. To address this problem, we have developed a novel error resilient packetization scheme. We first construct a Non-Redundant Directed Acyclic Graph to encode the dependencies among the vertex splits of a progressive mesh. A special Global Graph Equipartition Packing Algorithm is then applied to partitioning this graph into several equal size sub-graphs, which is packed as packets. The packing algorithm comprises two main phases: initial partition phase and global refinement phase. Experimental results demonstrate that the proposed scheme can minimize the dependencies between packets. Hence, it reduces the delay in rendering 3D models with proper quality at the clients.

We present a general framework for a higher-order spline level-set (HLS) method and apply this to biomolecule surfaces construction. Starting from a first order energy functional, we obtain a general level set formulation of geometric partial differential equation, and provide an efficient approach to solving this partial differential equation using a $C^2$ spline basis. We also present a fast cubic spline interpolation algorithm based on convolution and the Z-transform, which exploits the local relationship of interpolatory cubic spline coefficients with respect to given function data values. One example of our HLS method is demonstrated, which is the construction of biomolecule surfaces (an implicit solvation interface) with their individual atomic coordinates and solvated radii as prerequisites.

This paper describes the design-for-testability (DFT) features and low-cost testing solutions of a general purpose microprocessor. The optimized DFT features are presented in detail. A hybrid scan compression structure was executed and achieved compression ratio more than ten times. Memory built-in self-test (BIST) circuitries were designed with scan collars instead of bitmaps to reduce area overheads and to improve test and debug efficiency. The implemented DFT framework also utilized internal phase-locked loops (PLL) to provide complex at-speed test clock sequences. Since there are still limitations in this DFT design, the test strategies for this case are quite complex, with complicated automatic test pattern generation (ATPG) and debugging flow. The sample testing results are given in the paper. All the DFT methods discussed in the paper are prototypes for a high-volume manufacturing (HVM) DFT plan to meet high quality test goals as well as slow test power consumption and cost.