Solving Energy-Latency Dilemma: Task Allocation for Parallel Applications in Heterogeneous Embedded Systems
Parallel applications with energy and low-latency constraints are emerging in various networked embedded systems like digital signal processing, vehicle tracking, and infrastructure monitoring. However, conventional energy-driven task allocation schemes for a cluster of embedded nodes only concentrate on energy-saving when making allocation decisions. Consequently, the length of the schedules could be very long, which is unfavorable or in some situations even not tolerated. In this paper, we address the issue of allocating a group of parallel tasks on a heterogeneous embedded system with an objective of energy-saving and short-latency. A novel task allocation strategy, or BEATA (balanced energy-aware task allocation), is developed to find an optimal allocation that minimizes overall energy consumption while confining the length of schedule to an ideal range. Experimental results show that BEATA significantly improves the performance of embedded systems in terms of energy-saving and schedule length over an existing allocation scheme

title: Dynamic relocation of hybrid tasks: Strategies and methodologies
abstract: Reconfiguration-based architectures are increasingly gaining attention of designers due to their benefits of flexibility, re-programmability and high computational performance. The combination of general purpose processors and reconfigurable fabrics (e.g., FPGAs), may provide those valuable characteristics, which are becoming essential for modern and future embedded systems. Such hybrid systems permit the existence of hardware tasks, which shall be properly managed by the operating system, thus allowing for their coexistence with software tasks. Nevertheless, in order to completely exploit this feature, the operating system must be capable of relocating a task between hardware and software execution domains. Runtime relocation of tasks (including preemption and resumption) between two devices following different computation paradigms (parallel vs. instruction based) however is a challenging job. In this work we propose a comprehensive and embracing methodology, which starts from a unified task representation, and goes to the final implementation of such hybrid tasks. For its accomplishment, a framework is proposed to help the user in designing a hybrid task, which also generates automatically the underlying infrastructure that is in charge of performing the dynamic relocation of a hybrid task. In order to prove the applicability of our concept and the efficiency of our framework, a case study is presented including its results.

title: A Security-Oriented Task Scheduler for Heterogeneous Distributed Systems
abstract: High quality of security is increasingly critical for applications running on heterogeneous distributed systems, where processors operate at different speeds and communication channels have different bandwidths. Although there are a few scheduling algorithms in the literature for heterogeneous distributed systems, they generally do not take into account of security requirements of applications. In this paper, we propose a novel heuristic scheduling algorithm, or SATS, which is conducive to improving security of heterogeneous distributed systems. First, we formalize a concept of security heterogeneity for our scheduling model in the context of distributed systems. Next, we devise the SATS algorithm aiming at scheduling tasks to maximize the probability that all tasks are executed without any risk of being attacked. Empirical results demonstrate that with respect to security and performance, the proposed scheduling algorithm outperforms existing approaches for heterogeneous distributed systems.

title: PEARL: Performance, Energy, and Reliability Balanced Dynamic Data Redistribution for Next Generation Disk Arrays
abstract: Contemporary disk arrays consist purely of hard disk drives, which normally provide huge storage capacities with low-cost and high-throughput for data-intensive applications. Nevertheless, they have some inhenrent disadvantages such as long access latencies, high annual disk replacement rates, fragile physical characteristics, and energy-inefficiency due to their build-in mechanical and electronic mechanisms. Flash-memory based solid state disks, on the other hand, although currently more expensive and inadequate in write cycles, offer much faster aread accesses and are much more robust and energy efficient. To combine the complementary merits of hard disks and flash disks, in this paper we propose a hybrid disk array architecture named HIT (hybrid disk storage) for data-intensive applications. Next, a dynamic data redistribution strategy called PEARL (performance, energy, and reliability balanced), which can periodically redistribute data between flash and hard disks to adapt to the changing data access patterns, is developed on top of the HIT architecture.

title: Modeling and improving security of a local disk system for write-intensive workloads
abstract: Since security is of critical importance for modern storage systems, it is imperative to protect stored data from being tampered with or disclosed. Although an increasing number of secure storage systems have been developed, there is no way to dynamically choose security services to meet disk requests' flexible security requirements. Furthermore, existing security techniques for disk systems are not suitable to guarantee desired response times of disk requests. We remedy this situation by proposing an adaptive strategy (referred to as AWARDS) that can judiciously select the most appropriate security service for each write request, while endeavoring to guarantee the desired response times of all disk requests. To prove the efficiency of the proposed approach, we build an analytical model to measure the probability that a disk request is completed before its desired response time. The model also can be used to derive the expected value of disk requests' security levels. Empirical results based on synthetic workloads as well as real I/O-intensive applications show that AWARDS significantly improves overall performance over an existing scheme by up to 358.9% (with an average of 213.4%).

title: Scheduling security-critical real-time applications on clusters
abstract: Security-critical real-time applications such as military aircraft flight control systems have mandatory security requirements in addition to stringent timing constraints. Conventional real-time scheduling algorithms, however, either disregard applications' security needs and thus expose the applications to security threats or run applications at inferior security levels without optimizing security performance. In recognition that many applications running on clusters demand both real-time performance and security, we investigate the problem of scheduling a set of independent real-time tasks with various security requirements. We build a security overhead model that can be used to reasonably measure security overheads incurred by the security-critical tasks. Next, we propose a security-aware real-time heuristic strategy for clusters (SAREC), which integrates security requirements into the scheduling for real-time applications on clusters. Further, to evaluate the performance of SAREC, we incorporate the earliest deadline first (EDF) scheduling policy into SAREC to implement a novel security-aware real-time scheduling algorithm (SAEDF). Experimental results from both real-world traces and a real application show that SAEDF significantly improves security over three existing scheduling algorithms (EDF, least laxity first, and first come first serve) by up to 266.7 percent while achieving high schedulability.

title: Approximate Top-k Structural Similarity Search over XML Documents
abstract: With the development of XML applications, such as Digital Library, XML subscribe/publish system, and other XML repositories, top-k structural similarity search over XML documents is attracting more attention. The similarity of two XML documents can be measured by using the edit distance defined between XML trees in previous work. Since the computation of edit distances is time consuming, some recent work presented some approaches to calculate edit distance by using structural summaries to improve the algorithm performance. However, most existing algorithms for calculating edit distance between trees ignore the fact that nodes in a tree may be of different significance, and the same edit operation costs are assumed inappropriately for all nodes in XML document tree. This paper addresses this problem by proposing a summary structure which could be used to make the tree-based edit distance more rational; furthermore, a novel weighting scheme is proposed to indicate that some nodes are more important than others with respect for structural similarity. We introduce a new cost model for computing structural distance and takes weight information into account for nodes in distance computation in this paper. Compared with former techniques, our approach can approximately answer the top-k queries efficiently. We verify this approach through a series of experiments, and the results show that using weighted structural summaries for top-k queries is efficient and practical.

title: ACGT - A Comparative Genomics Tool
abstract: ACGT (a comparative genomics tool) is a genomic DNA sequence comparison viewer and analyzer. It can read a pair of DNA sequences in GenBank, Embl or Fasta formats, with or without a comparison file, and provide users with many options to view and analyze the similarities between the input sequences. It is written in Java and can be run on Unix, Linux and Windows platforms.


AVAILABILITY
The ACGT program is freely available with documentation and examples at website: