14893914
Energy-balanced task allocation for collaborative processing in networked embedded systems
In this paper, we study the problem of allocating a real-time application onto a set of homogeneous processing elements connected by a single-hop wireless network. A periodic application consisting of a set of communicating tasks is considered. Each element is equipped with discrete dynamic voltage scaling for exploring the energy-latency tradeoffs. The time and energy costs of both computation and communication activities are considered. The goal is to balance the energy dissipation of the elements during each period of the application with respect to the remaining energy of elements, such that the system lifetime is maximized. An Integer Linear Programming (ILP) formulation is first developed, which can be solved to obtain the optimal solution. We then propose an efficient 3-phase heuristic. Experimental results show that for small scale problems, the performance of the heuristic achieves up to 85% of the system lifetime obtained by the ILP-based approach. For large scale problems, the performance of the heuristic shows an improvement of 120-250\% in the system lifetime compared with the case where no voltage scaling is used. Further, we present two extensions of our approaches that consider multiple communication channels and techniques for exploring the energy-latency tradeoffs of the communication activities.
6740690
An integer programming approach for static mapping of paths onto heterogeneous real-time systems
In this paper, we study the problem of mapping a set of independent paths onto a heterogeneous real-time system. Each path is a pipeline of several stages where each stage consists of one application. Each path has latency and throughput requirements that have to be satisfied. The general goal of this problem is to find an initial static mapping of all applications onto available system resources to maximize the allowable increase in input load, until dynamic remapping is required to avoid Quality of Service (QoS) violations on any path. The objective function considered in this paper is to find a static mapping such that the sum of the latencies of all paths is minimized, while satisfying all latency and throughput requirements. The motivation behind it is to give more room for each path to accommodate additional load at run-time. We develop an integer programming (IP) formulation for modeling this mapping problem. By solving the formulation, a feasible mapping can be found that satisfies latency and throughput requirements of all paths and optimizes the objective function. Two heuristics are given along with the IP formulation to provide efficient solutions. Experimental results show the correctness of the IP formulation and the effectiveness of our heuristics.
17834421
Querying sensor networks using ad hoc mobile devices: A two-layer networking approach
An interplay between mobile devices and static sensor nodes is envisioned in the near future. This will enable a heterogeneous design space that can offset the stringent resource and power constraints encountered in traditional static sensor networks by taking advantage of the more powerful mobile devices. We present a systematic framework for end-to-end query processing, using a two-layer architecture that consists of mobile devices at the upper layer and static sensor nodes at the bottom layer. The framework employs a ''PULL'' query model that contains staged operations including query generation, query routing, query injection, and query result routing. Each of these stages of query processing is discussed with an emphasis on techniques for energy-efficient query injection and query result routing with location-ignorant sensor nodes. The techniques leverage the mobility and transmission flexibility of mobile objects at the upper layer. Numeric and simulation results are provided to support the proposed methods.
29456782
Query privacy in wireless sensor networks
Existing mechanisms for querying wireless sensor networks leak client interests to the servers performing the queries. The leaks are not only in terms of specific regions but also of client access patterns. In this paper we introduce the problem of preserving the privacy of clients querying a wireless sensor network owned by untrusted organizations. We investigate two architectures and their corresponding trust models. For the first model, consisting of multiple, mutually distrusting servers governing the network, we devise an efficient protocol, SPYC, and show that it provides full query privacy. For the second model, where all queries are performed through a single server, we introduce two metrics for quantifying the privacy achieved by a client's query sequence. We propose a suite of practical algorithms, then analyze the privacy and efficiency levels they provide. Our TOSSIM simulations show that the proposed query mechanisms are communication efficient while significantly improving client query privacy levels.
15504838
Utilization-based heuristics for statically mapping real-time applications onto the HiPer-D heterogeneous computing system
Real-time applications continue to increase in importance as they are employed in various critical areas, such as command and control systems. These applications have traditionally required custom-made systems to execute them. Recently, with the widespread use of increasingly powerful commercial off-the-shelf (COTS) products, some real-time system designers have started a shift from custom development to COTS-based systems to achieve lower costs and more flexible systems. This research investigates the problem of allocating real-time applications to a set of COTS heterogeneous machines connected together by a COTS high-speed network. The heuristics were implemented on the High Performance Distributed Computing Program's (HiPer-D) Naval Surface Warfare Center (NSWC) testbed. At the specification of NSWC, the goal of this study is to design static resource allocation heuristics that balance the utilization of the computation and network resources in the HiPer-D system based on the system information provided. The broader goal is to maximize the time before dynamic reallocation is required for managing an increased workload at runtime.
12506111
A Case Study in Integrating Multiple E-commerce Standards via Semantic Web Technology
Internet business-to-business transactions present great challenges in merging information from different sources. In this paper we describe a project to integrate four representative commercial classification systems with the Federal Cataloging System (FCS). The FCS is used by the US Defense Logistics Agency to name, describe and classify all items under inventory control by the DoD. Our approach uses the ECCMA Open Technical Dictionary (eOTD) as a common vocabulary to accommodate all different classifications. We create a semantic bridging ontology between each classification and the eOTD to describe their logical relationships in OWL DL. The essential idea is that since each classification has formal definitions in a common vocabulary, we can use subsumption to automatically integrate them, thus mitigating the need for pairwise mappings. Furthermore our system provides an interactive interface to let users choose and browse the results and more importantly it can translate catalogs that commit to these classifications using compiled mapping results.
33694964
Workflow scheduling in grids: an ant colony optimization approach
Grid applications in virtue of open service grid architecture (OGSA) are promising next-generation computation techniques. One of the most important and challenging problems about grid application is the workflow scheduling problem to achieve the users' QoS (quality of service) requirements as well as to minimize the cost. This paper proposes an ant colony optimization (ACO) algorithm to tackle this problem. Several new features are introduced to the algorithm. First, we define two kinds of pheromone and three kinds of heuristic information to guide the search direction of ants for this bi-criteria problem. Each ant uses either one from these heuristic types and pheromone types in each iteration based on the probabilities controlled by two parameters. These two parameters are adaptively adjusted in the process of the algorithm. Second, we use the information of partial solutions to modify the bias of ants so that inferior choices will be ignored. Moreover, the experimental results in 3 workflow applications under different deadline constraints show that the performance of our algorithm is very promising, for it outperforms the Deadline-MDP algorithm in most cases.
34996951
Dynamic Multi-reference Prediction in Video Coding for Improved Error Resilience over Internet
When standard coded video is transmitted over Internet where packets may be lost, there exist the annoying problem of error propagation. In this paper we propose a new video coding scheme that dynamically chooses multireference prediction (DMRP). Based on the system model of the video codec with DMRP, we derive that the more candidate frames from which the references are chosen, the greater error resilience is achieved. Specifically we study the performance of video coding with two references selected from four candidate frames (2R4CF). The simulation results under the typical packet loss rates of Internet show that video coding with 2R4CF provides better error resilience than fixed two-reference video coding [4], single-reference four-frame video coding [3] and H.263 standard coding [5] with the coding efficiency nearly the same or a little higher than H.263 standard coding.
15248817
TEFE: A Time-Efficient Approach to Feature Extraction
With the rapid evolution of Internet applications, people all over the world are sharing pictures, videos and audios online, and thus, content-based analysis is often demanded. Test efficiency is crucial to the success of online information processing. One obstacle to high-speed testing is the time cost of feature extraction for test objects, particularly for objects with complex representation such as images, videos and audios. In this paper, we study the problem of reducing test time cost by extracting cheap but sufficient features. We propose the TEFE (time-efficient feature extraction) approach, which balances between the test accuracy and test time cost by extracting a proper subset of features for each test object. In the implementation, TEFE trains a sequence of support vector machines and classifies each test object cascadingly. Empirical study shows that TEFE is time efficient while holding a classification accuracy close to that of using all features. It also shows that the test time is linearly adjustable in TEFE.
9176644
Automated and safe vulnerability assessment
As the number of system vulnerabilities multiplies in recent years, vulnerability assessment has emerged as a powerful system security administration tool that can identify vulnerabilities in existing systems before they are exploited. Although there are many commercial vulnerability assessment tools in the market, none of them can formally guarantee that the assessment process never compromises the computer systems being tested. This paper proposes a featherweight virtual machine (FVM) technology to address the safety issue associated with vulnerability testing. Compared with other virtual machine technologies, FVM is designed to facilitate sharing between virtual machines but still provides strong protection between them. The FVM technology allows a vulnerability assessment tool to test an exact replica of a production-mode network service, including both hardware and system software components, while guaranteeing that the production-mode network service is fully isolated from the testing process. In addition to safety, the vulnerability assessment support system described in this paper can also automate the entire process of vulnerability testing and thus for the first time makes it feasible to run vulnerability testing autonomously and frequently. Experiments on a Windows-based prototype show that Nessus assessment results against an FVM virtual machine are identical to those against a real machine. Furthermore, modifications to the file system and registry state made by vulnerability assessment runs are completely isolated from the host machine. Finally, the performance impact of vulnerability assessment runs on production network services is as low as 3%