Atakan Dogan

Matching and scheduling algorithms for minimizing execution time and failure probability of applications in heterogeneous computing

In a heterogeneous distributed computing system, machine and network failures are inevitable and can have an adverse effect on applications executing on the system. To reduce the effect of failures on an application executing on a failure-prone system, matching and scheduling algorithms which minimize not only the execution time but also the probability of failure of the application must be devised. However, because of the conflicting requirements, it is not possible to minimize both of the objectives at the same time. Thus, the goal of this paper is to develop matching and scheduling algorithms which account for both the execution time and the reliability of the application. This goal is achieved by modifying an existing matching and scheduling algorithm. The reliability of resources is taken into account using an incremental cost function proposed in this paper and the new algorithm is referred to as the reliable dynamic level scheduling algorithm. The incremental cost function can be defined based on one of the three cost functions developed here. These cost functions are unique in the sense that they are not restricted to tree-based networks and a specific matching and scheduling algorithm. The simulation results confirm that the proposed incremental cost function can be incorporated into matching and scheduling algorithms to produce schedules where the effect of failures of machines and network resources on the execution of the application is reduced and the execution time of the application is minimized as well.

LDBS: a duplication based scheduling algorithm for heterogeneous computing systems

Finding an optimal solution to the problem of scheduling an application modeled by a directed acyclic graph (DAG) onto a set of heterogeneous machines is known to be an NP-hard problem. In this study, we present a duplication based scheduling algorithm, namely the levelized duplication based scheduling (LDBS) algorithm, which solves this problem efficiently. The primary goal of LDBS is to minimize the schedule length of applications. LDBS can accommodate different duplication heuristics, thanks to its modular design. Specifically, we have designed two different duplication heuristics with different time complexities. The simulation studies confirm that LDBS is a very competitive scheduling algorithm in terms of minimizing the schedule length of applications.

Scheduling Independent Tasks with QoS Requirements in Grid Computing with Time-Varying Resource Prices

This paper considers the problem of scheduling a set of independent tasks with multiple QoS requirements, which may include timeliness, reliability, security, version, and priority, in a Grid computing system in which resource prices can vary with time during scheduling time intervals. This problem is referred to as the QoS-based scheduling problem with time-varying resource prices. In order to solve this problem, a static scheduling algorithm (QSMTS VP) is developed. The simulation studies carried out show that QSMTS VP is capable of meeting diverse QoS requirements of many users simultaneously and that QSMTS VP can react to the dynamics of the market. Thus, QSMTS VP is a promising heuristic that can be deployed in a computational market.

Reliable matching and scheduling of precedence-constrained tasks in heterogeneous distributed computing

In this paper, two cost functions that can be incorporated into a matching and scheduling algorithm for tasks with precedence constraints are introduced to enable the algorithm to consider the reliability of different resources in the system while making decisions. The cost functions introduced are unique in the sense that they are not restricted to tree-based networks and a specific matching and scheduling algorithm. As an example, cost functions are applied to a compile time, static list scheduling heuristic. The simulation results confirm that the proposed cost functions can be exploited to produce task assignments where the effect of failures of machines and network resources on the execution of the application is reduced.

On QoS-based scheduling of a meta-task with multiple QoS demands in heterogeneous computing

This paper investigates the problem of scheduling a set of independent tasks with multiple QoS needs, which may include timeliness, reliability, security, data accuracy, and priority, in a heterogeneous computing system. This problem is referred to as the QoS-based scheduling problem and proven to be NP-hard. In order to solve the QoS-based scheduling problem, a computationally efficient static scheduling algorithm (QSMTS_IP) is developed. The simulation studies carried out show that QSMTS_IP is capable of meeting diverse QoS requirements of marry users simultaneously, while minimizing the number of users whose tasks cannot be scheduled due to the scarcity of resources.

MAC layer protocols for real-time traffic in ad-hoc wireless networks

Providing quality of service (QoS) to high bandwidth video, voice and data applications in wireless networks is an important problem. Such applications are in the class of real-time applications; they need communication operations to complete within certain targeted deadlines. Based on this premise, this paper addresses the design of distributed MAC layer protocols that incorporate explicit support for real-time traffic in an ad-hoc wireless network. Specifically, we have developed two new MAC layer protocols, namely the elimination by sieving (ES-DCF) and the deadline bursting (DB-DCF) protocols. Both algorithms use deterministic collision resolution algorithms in order to provide timely delivery guarantees to different classes of real-time traffic. The extensive simulation studies conducted confirmed that ES-DCF and DB-DCF perform well for hard-real-time traffic and soft-real-time traffic, respectively.

Optimal and suboptimal reliable scheduling of precedence-constrained tasks in heterogeneous distributed computing

Introduces algorithms which can produce both optimal and suboptimal task assignments to minimize the probability of failure of an application executing on a heterogeneous distributed computing system. A cost function which defines this probability under a given task assignment is derived. To find optimal and suboptimal task assignments efficiently, a reliable matching and scheduling problem is converted into a state-space search problem in which the cost function derived is used to guide the search. The A* algorithm for finding optimal task assignments and the A*/sub m/ and hill-climbing algorithms for finding suboptimal task assignments are presented. Simulation results are provided to confirm the performance of the proposed algorithms.

Routing in wormhole-switched clustered networks with applications to fault tolerance

This paper presents a novel technique for routing in wormhole-switched multiprocessor interconnection networks with clustered configuration. The network model used here consists of a set of clusters interfaced through a common central network. We assume that the central network and the clusters use independent algorithms to route messages between their internal nodes. A technique for deriving a global routing algorithm based on the local algorithms is presented, which allows the transfer of messages between any pair of nodes in the network. This proposed method is shown to be deadlock-free with two virtual channels. The clustered network model and the proposed routing technique can be used to enhance the fault tolerance capability of existing routing algorithms. In particular, we describe fault-tolerant routing methods for meshes, which can tolerate any arbitrary fault distribution without disabling connected healthy nodes.

An urgency-based prioritized MAC layer protocol for real-time traffic in ad-hoc wireless networks

This paper presents a distributed MAC layer protocol, prioritization by urgency - DCF (PU-DCF), which incorporates explicit support for real-time traffic in ad-hoc wireless networks. In PU-DCF, a packets priority is updated dynamically according to its priority level and urgency (or laxity). Two collision resolution algorithms (CRAs) are proposed to guarantee timely delivery of packets. Simulations show that the proposed protocol performs well for hard real-time (HRT) traffic and has stable performance even when the channel is overloaded. Furthermore, several simulation scenarios are designed to discuss the effect of several system parameters and compare the performance of the two CRAs.