Füsun Özgüner

Urban multi-hop broadcast protocol for inter-vehicle communication systems

Inter-Vehicle Communication Systems rely on multi-hop broadcast to disseminate information to locations beyond the transmission range of individual nodes. Message dissemination is especially difficult in urban areas crowded with tall buildings because of the line-of-sight problem. In this paper, we propose a new efficient IEEE 802.11 based multi-hop broadcast protocol (UMB) which is designed to address the broadcast storm, hidden node, and reliability problems of multi-hop broadcast in urban areas. Thisprotocol assigns the duty of forwarding and acknowledging broadcast packet to only one vehicle by dividing the road portion inside the transmission range into segments and choosing the vehicle in the furthest non-empty segment without apriori topology information. When there is an intersection in the path of the message dissemination, new directional broadcasts are initiated by the repeaters located at the intersections. We have shown through simulations that our protocol has a very high success rate and efficient channel utilization when compared with other flooding based protocols.

Partitioning based mobile element scheduling in wireless sensor networks

In recent studies, using mobile elements (MEs) as mechanical carriers of data has been shown to be an effective way of prolonging sensor network life time and relaying information in partitioned networks. As the data generation rates of sensors may vary, some sensors need to be visited more frequently than others. In this paper, a partitioning-based algorithm is presented that schedules the movements of MEs in a sensor network such that there is no data loss due to buffer overflow. Simulation results show that the proposed Partitioning Based Scheduling (PBS) algorithm performs well in terms of reducing the minimum required ME speed to prevent data loss, providing high predictability in inter-visit durations, and minimizing the data loss rate for the cases when the ME is constrained to move slower than the minimum required ME speed.

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.

Statistical prediction of task execution times through analytic benchmarking for scheduling in a heterogeneous environment

In this paper, a method for estimating task execution times is presented in order to facilitate dynamic scheduling in a heterogeneous metacomputing environment. Execution time is treated as a random variable and is statistically estimated from past observations. This method predicts the execution time as a function of several parameters of the input data and does not require any direct information about the algorithms used by the tasks or the architecture of the machines. Techniques based upon the concept of analytic benchmarking/code profiling are used to characterize the performance differences between machines, allowing observations from dissimilar machines to be used when making a prediction. Experimental results are presented which use actual execution time data gathered from 16 heterogeneous machines.

Black-Burst-Based Multihop Broadcast Protocols for Vehicular Networks

In this paper, two IEEE 802.11-based multihop broadcast protocols, namely urban multihop broadcast and ad hoc multihop broadcast, are proposed to address the broadcast storm, hidden node, and reliability problems of multihop broadcast in vehicular networks. In the proposed protocols, the functions of forwarding and acknowledging the broadcast packet are assigned to only one vehicle by dividing the road portion inside the transmission range into segments and choosing the vehicle in the furthest nonempty segment without a priori topology information. The simulation results confirm that our protocols have very high success rate and efficient channel utilization when compared with other flooding-based protocols. It is also concluded that there is no need for infrastructure support unless the line of sight among different road segments incident to an intersection is blocked with obstacles.

Biobjective Scheduling Algorithms for Execution Time–Reliability Trade-off in Heterogeneous Computing Systems *

A heterogeneous computing (HC) system is composed of a suite of geographically distributed high-performance machines interconnected by a high-speed network, thereby providing high-speed execution of computationally intensive applications with diverse demands. In HC systems, however, there is a possibility of machine and network failures and this can have an adverse impact on applications running on the system. In order to decrease the impact of failures on an application, matching and scheduling algorithms must be devised which minimize not only the execution time but also the failure probability of the application. However, because of the conflicting requirements, it is not possible to minimize both 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 failure probability and can trade off execution time against the failure probability of the application. In order to attain these goals, a biobjective scheduling problem is first formulated and then two different algorithms, the biobjective dynamic level scheduling algorithm and the biobjective genetic algorithm, are developed. Unique to both algorithms is the expression used for computing the failure probability of an application with precedence constraints. The simulation results confirm that the proposed algorithms can be used for producing task assignments where the execution time is weighed against the failure probability.

Energy-constrained task mapping and scheduling in wireless sensor networks

Collaboration among sensors through parallel processing mechanisms emerges as a promising solution to achieve high processing power in resource-restricted wireless sensor networks (WSN). Although task mapping and scheduling in wired networks of processors has been well studied in the past, their application to WSNs remains largely unexplored. Due to the limitations of WSNs, existing algorithms cannot be directly implemented in WSNs. In this paper, a task mapping and scheduling solution for energy-constrained applications in WSNs, energy-constrained task mapping and scheduling (EcoMapS), is presented. EcoMapS incorporates channel modeling, concurrent task mapping, communication and computation scheduling, and sensor failure handling algorithm. The performance of EcoMapS is evaluated through simulations with randomly generated directed acyclic graphs (DAG). Simulation results show significant performance improvements compared with an existing mechanism in terms of minimizing schedule lengths subject to energy consumption constrains

Dynamic, competitive scheduling of multiple DAGs in a distributed heterogeneous environment

With the advent of large scale heterogeneous environments, there is a need for matching and scheduling algorithms which can allow multiple DAG-structured applications to share the computational resources of the network. The paper presents a matching and scheduling framework where multiple applications compete for the computational resources on the network. In this environment, each application makes its own scheduling decisions. Thus, no centralized scheduling resource is required. Applications do not need direct knowledge of the other applications. The only knowledge of other applications arrives indirectly through load estimates (like queue lengths). The paper also presents algorithms for each portion of this scheduling framework. One of these algorithms is modification of a static scheduling algorithm, the DLS algorithm, first presented by Sih and Lee (1993). Other algorithms attempt to predict the future task arrivals by modeling the task arrivals as Poisson random processes. A series of simulations are presented to examine the performance of these algorithms in this environment. These simulations also compare the performance of this environment to a more conventional, single user environment.

An Efficient Fully Ad-Hoc Multi-Hop Broadcast Protocol for Inter-Vehicular Communication Systems

In this paper, a fully Ad-Hoc Multi-hop Broadcast protocol (AMB) is proposed for inter-vehicular networks. The AMB is an ad-hoc extension of the UMB protocol which handles broadcast in intersections with the help of repeaters. The AMB protocol eliminates the most important drawback - infrastructure dependence - of the UMB protocol by employing an efficient intersection broadcast mechanism. When there is an intersection in the path of the message dissemination, new directional broadcasts to all road segments are initiated by the vehicle closest to the intersection with a fully ad-hoc algorithm without apriori topology information. The simulation results confirm that our protocol has a very high success rate and efficient channel utilization. Consequently, it is concluded that there is no need for infrastructure support unless the the line-of-sight among different road segments incident to an intersection is blocked with obstacles.

Run-time statistical estimation of task execution times for heterogeneous distributed computing

An efficient run time, statistical scheme for estimating the execution time of a task is presented, in order to facilitate run time matching and scheduling in a distributed heterogeneous computing environment. This scheme is based upon a nonparametric regression technique, where the execution time estimate for a task is computed from past observations. Furthermore, this technique is able to compensate for different parameters upon which the execution time depends, and does not require any knowledge of the architecture of the target machine. It is also able to make accurate predictions when erroneous data is present in the set of observations, and has been experimentally shown to produce estimates with very low error even with few past values from which to calculate a new estimate.