Maximizing the aggregate network performance over constrained computing and communication resources has been an active research area. Real-time wireless sensor network (RTWSN) is an important application of real-time and networked embedded systems. Due to the severe resources constraints and associated real-time requirements, new challenges arise in RTWSN. In this paper, we study an integrated scheme to optimize the total system performance of real-time flows over an RTWSN by exploiting multi-path routing and dynamic sampling rate assignment. We formally model the problem using nonlinear optimization and design an online distributed algorithm to obtain the optimal rate assignments on multiple paths. Extensive simulation studies demonstrates the significant performance improvements over existing proposals.

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Although dynamic binary translators (DBT) are gaining popularity in the modern virtual execution environments (VEE), the requirement of DBTs' processing and memory resources has seriously hampered the performance of host platform. In this paper, we propose a distributed DBT system--DistriBit for resource-limited thin clients to overcome these challenges.

Counting or estimating the number of tags is crucial for RFID system. Researchers have proposed several fast cardinality estimation schemes to estimate the quantity of a batch of tags within a short time frame. Existing estimation schemes scarcely consider the privacy issue. Without effective protection, the adversary can utilize the responding signals to estimate the number of tags as accurate as the valid reader. To address this issue, we propose a novel privacy-preserving estimation scheme, termed as MEAS, which provides an active RF countermeasure against the estimation from invalid readers. MEAS comprises of two components, an Estimation Interference Device (EID) and two well-designed Interference Blanking Estimators (IBE). EID is deployed with the tags to actively generate interfering signals, which introduce sufficiently large estimation errors to invalid or malicious readers. Using a secret interference factor shared with EID, a valid reader can perform accurate estimation via two IBEs. Our theoretical analysis and simulation results show the effectiveness of MEAS. Meanwhile, MEAS can also maintain a high estimation accuracy using IBEs.

Complex web applications are usually served by multi-tier web clusters. With the growing cost of energy, the importance of reducing power consumption in server systems is now well-known and has become a major research topic. However, most of previous works focused solely on homogeneous clusters. This paper addresses the challenge of power management in Heterogeneous Multi-tier Web Clusters. We apply Generalized Benders Decomposition (GBD) to decompose the global optimization problem into small sub-problems. This algorithm achieves the optimal solution in an iterative fashion. The simulation results show that our algorithm achieve more energy conservation than the previous works.

In RFID systems, the reader is unable to discriminate concurrently reported IDs of tags from the overlapped signals, and a collision happens. Many algorithms for anticollision are proposed to improve the throughput and reduce the latency for tag identification. Existing anti-collision algorithms mainly employ CRC based collision detection functions for determining whether the collision happens. Generating CRC codes, however, requires complicated computations for both RF tags and readers, and hence incurs non-trivial time consumption, becoming the bottleneck. In this study, we design a Quick Collision Detection (QCD) scheme based on the bitwise complement function plus collision preamble, which significantly reduces the number of gates for computation and facilitates to simplify the IC design of RFID tags. The QCD scheme does not require any modification on upperlevel air protocols, so it can be seamlessly adopted by current anti-collision algorithms. Through comprehensive analysis and simulations, we show that QCD improves the identification efficiency by 40%.

This is the first workshop in CIKM conference that addresses the challenge of large data management based on cloud computing infrastructure. This workshop will bring together researchers and practitioners in cloud computing and data-intensive system design, programming, parallel algorithms, data management, scientific applications, and information-based applications to maximize performance, minimize cost and improve the scale of their endeavors.

Software rejuvenation is a preventive and proactive technology to counteract the phenomenon of software aging and system failures, and to improve the system reliability. In this paper we present a mixed software rejuvenation policy for an operational software system with multiple degradation states, which considers both the history information and the current running state. By this policy, the system is rejuvenated when it achieves to a degradation threshold or it comes to the pre-determined rejuvenation interval. For comparison, standard rejuvenation policy is also discussed. Continuous-time Markov chains are used to describe the multiple degradation states model. To evaluate these polices expediently, we utilize deterministic and stochastic Petri nets (DSPN) to solve the models. Numerical results show that the deployment of software rejuvenation in the system leads to significant improvement in availability and throughput. And the mixed rejuvenation policy is better than the standard rejuvenation policy.

The fundamental characteristics of SOA, loose coupling and on-demand integration, enable organizations to seek more flexibility and responsiveness from their business IT systems. However, this brings challenges to assure QoS, especially availability, which should be considered in an integrated way in an SOA environment. Traditionally, availability is measured for each IT resource, but within SOA environments, rather than being considered individually, availability should be analyzed from an end-to-end view from both business and IT perspectives. In this paper, to address the availability problem of SOA, we propose a methodology that analyzes availability weak points in SOA deployment frameworks, leveraging workflow definitions that specify availability requirements at business level. This methodology includes an effective way to calculate high availability enhancement recommendations for a given SOA deployment topology with near-minimum cost, while meeting the business-level availability requirements. A prototype has been implemented as an extension to IBM's SOA deployment framework. Its efficiency and performance are analyzed here.

With the increased interest in the Web services composition, more and more enterprises and businesses depend on this paradigm. Open, distributed and dynamic properties of the schema, there is a pressing need for secure services in daily transactions. Orchestration and choreography language provide basic services standards and interaction, collaboration, and negotiation standards among services, but they are not give any secure manners or secure operation styles and specifications. Despite the interest of such security mechanisms, a formal module of them is still lacking. For giving general guide to implement secure orchestration and choreography language, we give a formal approach to carry out those goals. To this target, we emphasize on those by designing an extension of the Spi calculus with Secure Global Calculus. The Spi calculus precisely identifies orchestration secure properties of each principal from a local viewpoint. The secure global calculus describes an interaction secure choreography scenario from a vantage point of view. We called our method SpiG4WSC calculus. We believe that the combination of strong practical needs for dynamic secure Web services composition and the theoretical foundations will lead to a bridge between practice and theories. The contribution of this paper are (1) giving the syntax and semantic of SpiG4WSC calculus; (2)applying the calculus to give a model to presenting the secure orchestration, emphasizing on the formal basis for secure services; (3)describing the secure choreography, giving the formal frame for interaction processes.

Service Oriented Architecture (SOA) and Service Oriented Computing (SOC) are prevailing paradigms for sharing and reusing resources. Service composition is a methodology widely used in SOA and SOC to build new value-added services on primitive services on-the-fly to support online Business-to-Business collaborations. Requirements of customers to these composite services include functionality and non-functionality. Since many services can have the similar functionality, the non-functionality of composite services, such as Quality of Services (QoS), is the important metrics to distinguish a service from each other and find an optimal program to meet the requirements of customers. This paper firstly proposes a system model from the view of resource and value, and then we introduce an improved heuristic algorithm for the selection of composite services with multiple constraints. The simulation experiments show an outperforming result of proposal algorithm in both utility performance and time cost comparing with the other heuristic algorithms.

Modern software model checkers are usually used to find safety violations. However, checking liveness properties can offer a more natural and effective way to detect errors, particularly in complex concurrent and distributed e-business systems. Specifying global liveness properties which should always eventually be true proves to be more desirable, but it is hard for existing software model checkers to verify liveness in real codes because doing so requires finding an infinite execution. For solving such a challenge, this paper proposes an online checking tool to verify the safety and liveness properties of complex systems. We adopt the linear temporal logic to describe the semantics of the finite model checking, use binary instrumentation to obtain the distribute states and apply a checking engine to dynamically verify the finite trace linear temporal logic properties. At last, we demonstrate the method in a distributed system using distributed protocol Paxos and achieve good results by experiments.

A generalized declarative constraint framework is proposed in this paper to address challenges of applying constraints to model-driven SOA deployment and configuration. By representing deployment metamodel and domain knowledge as patterns, constraints can be easily described, automatically validated and analyzed. This framework reduces the human-intensiveness and error-proneness in the activity of applying constraints to a SOA deployment topology. We implemented this framework over a model-driven SOA deployment platform leveraging OCL as the declarative constraint language, and verified it in industry deployment scenarios.

The proper operation of Service-Oriented Architecture (SOA) depends on underlying system services of operating systems, so efficient and effective migration of Service Hosting Environment is critical to cope with intrinsic-changed nature of SOA. However, due to the large amount of configuration items, complicated mapping and complex dependency relationship among system services, migrating into a new Service Hosting Environment satisfying the operation requirement of SOA becomes an error-prone and time-consuming task. The SCM project in IBM develops a novel approach to migrate Service Hosting Environment shaped in Unix-like systems. Firstly, this approach builds a set of configuration models to describe various system services. Then based on models, it presents knowledge based mapping to translate system service configurations between Service Hosting Environments. Finally, it designs a dependency hierarchy deducting algorithm to compute the dependency relationship among system services for migration traceability and error determination. A SCM prototype has performed well on largely reducing time, labor and errors in real migration cases.

Efficient problem detection methods play an important role in system management. In this paper, a formal method is described for problem detection in large scale and distributed enterprise IT environment. Events from distributed system components are collected, filtered and correlated. Leveraging these correlated events, the behavior of a distributed system is presented as a problem detection state machine (PDSM). PDSM is built up automatically from system logs without any specification of the target system. This approach combines logs from multi-sources and does not require any human involved or experimental instructions. It is generally applicable to a large class of distributed systems. Experimental results show that the implementation of PDSM performs problem detection efficiently in typical distributed enterprise systems.

Large data centers usually host many different services on a shared computing infrastructure, for which on-demand resource management is necessary to maximize providers' revenues by meeting service quality targets at least operational cost. This paper presents a novel architecture of autonomic resource management framework based on virtualized service-oriented computing (SOC) environment. A non-linear continuous optimization problem is defined for adaptive resource allocation and a model-based approach is adopted to solve this problem. Different from traditional approaches, the analytic model we established provides probabilistic performance guarantees and considers non-steady-state behavior assisted by admission control. Results of prototype experiments demonstrate that the performance of multiple services has been greatly improved by taking advantage of fine-grained resource sharing, while incurring much lower resource usage cost. Also, differentiated service qualities could be provided to different client classes through our dynamic resource allocation scheme.

Availability is one of the important factors to be considered for business-driven IT service management. This paper addresses the issue of analyzing what we call availability weak-points in an SOA deployment framework, leveraging workflow definitions to specify the high availability requirement at the business process level. In our weak-point analysis framework, we present an effective analysis methodology to calculate the optimal high availability solution with minimum cost, while meeting the business level availability requirements. We evaluate the weakpoint analysis methodology, and show that our methodology can identify a near-optimal solution for availability enhancement over the SOA deployment framework.

According to the characteristics of the operational behavior and runtime state of application sever, the resource consumption time series are observed and modeled by fuzzy wavelet network (FWN) with fuzzy logic inference and learning capability. The objective is to model the extracted data series of systematic performance parameters to predict software aging in application server. The dimensionality of input variables of FWN is reduced by principal components analysis (PCA), and the structure and parameters of FWN are optimized with adaptive genetic algorithm (GA). Judging by the model, we can get the aging threshold before application server failed and preventively maintenance the application server before systematic parameter value reaches the threshold. The experiments are carried out to validate the efficiency of the proposed model and show that the aging prediction model based on FWN with adaptive genetic algorithm is superior to the neural network (NN) model and wavelet network (WN) model in the aspects of convergence rate and prediction precision

XML plays an important role in building enterprise applications. However, most of the XML-based applications, particularly the emerging Web services, suffer from low performance caused by XML processing and thus bring negative user experience in terms of response time. We argue that by reducing the considerable overhead in garbage collection the XML processing performance can be improved. We begin by conducting a set of experiments to understand the XML parser's memory characteristics, such as heap composition, object size and type distributions, object lifetime, and so on. Then, we get the valuable findings for improving performance that XML processing, which violates the weak generational hypothesis, is a memory allocation intensive workload in which most objects are small and long-lived. The findings can benefit the design of XML parsing specific GC and related tools designed to improve XML processing performance for Web services

The configuration of a service-based system has a significant impact on the nonfunctional requirements of the system as a whole. However, finding the best configuration is very challenging and sometimes impossible for administrators because so many factors have to be considered. More importantly, a service based system has to be frequently reconfigured to adapt to rapid and continuous changes in user requirements and runtime environments. In this paper we propose an autonomic computing approach to the problem of reconfiguration, that is, enabling the service based system to configure itself by means of a loop of monitoring, analyzing, planning and executing actions. We begin by formalizing the definition of configuration and reconfiguration. Then, we describe how we implemented the autonomic computing mechanisms for reconfiguring service-based systems to satisfy service level agreements with minimal resource consumption. The approach is demonstrated on a resilient service provisioning environment. Finally, the preliminary experiments are evaluated to determine the effectiveness of proposed approach.

The dynamic nature of the Grid environment brings challenges to the services provisioning technique. A major aspect of Grid is to match demands for services with resources. Since resources and demands are fluctuating, Grid services provisioning need to be adjusted accordingly in responding to changes. In this paper, we propose a novel approach, Grid services migration, to enabling services provisioning on demand. The major motivation is to achieve the desired Quality of Service (QoS) such as performance, reliability, and etc. of Grid services on resources assembled dynamically responding to dynamic demand. In this paper, the technical characteristics of Grid services migration and its taxonomy are introduced. The Grid service migration algorithms are also presented. The Grid services migration framework with MAPE (Monitor, Analyze, Plan, and Execute) loop is proposed based on Open Grid Services Architecture (OGSA) and the prototype named Services Ecosystem, a resilient infrastructure for services provisioning on demand in Grid is developed. Demonstrations and experiments are conducted and results are presented to illustrate the capabilities of Grid services migration.

In this paper, we propose the concepts of virtual partner and inspector into the Web services composition. Virtual partner, as an IT level concept, is a Web service (pseudo Web service) using the same interface with the actual partner but different binding message. A virtual partner can be invoked directly by a business process described by BPEL, so that the BPEL programmer can test both application's functionality and non functionality performance early in the development cycle to avoid any problems in the final runtime, or test the selection of their partners in business level design. The IT virtual partners provide developers with a range of the techniques which let them explore every aspect of their program. Inspector is proposed when using the third-party process engine. An inspector itself is also a Web service. The programmer can register any required output information in it. The IT virtual partner and the inspector concepts have been integrated in our WSCE, a flexible Web Services Composition Environment for a business process. WSCE is a prototype of autonomic modeling and simulation environment. With the help of a third-party BPEL engine, it provides programmer with concepts and tools to facilitate business process programming.

Data warehouse and Online Analytical Processing(OLAP) play a key role in business intelligent systems. With the increasing amount of spatial data stored in business database, how to utilize these spatial information to get insight into business data from the geo-spatial point of view is becoming an important issue of data warehouse and OLAP. However, traditional data warehouse and OLAP tools can not fully exploit spatial data in coordinates because multi-dimensional spatial data does not have implicit or explicit concept hierarchy to compute pre-aggregation and materialization in data warehouse. In this paper we extend the traditional set-grouping hierarchy into multi-dimensional data space and propose to use spatial index tree as the hierarchy on spatial dimension. With spatial hierarchy, spatial data warehouse can be built accordingly. Our approach preserve the star schema in data warehouse while building the hierarchy on spatial dimension, and can be easily integrated into existing data warehouse and OLAP systems. To process spatial OLAP query in spatial data warehouse, we propose an OLAP-favored search method which can utilize the pre-aggregation result in spatial data warehouse to improve the performance of spatial OLAP queries. For generality, the algorithm is developed based on Generalized Index Searching Tree(GiST). To improve the performance of OLAP-favored search, we further introduce a heuristic search method which can provide an approximate answer to spatial OLAP query. Experiment result shows the efficiency of our method.

BlueLocator, a framework enabling enterprise location-based services as well as an enterprise user locating and tracking system, is introduced in this paper. Privacy control in LBS is discussed and a report-to-chain based access control list assignment policy is shown as an example of how a privacy related rule can be used for applications.