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17th IEEE International Conference on Mobility, Sensing and Networking (MSN)

作者： Wu, Qiong Liu, Zhenming William & Mary Williamsburg VA 23185 USA

ISBN: (纸本)9781665406680

Large-scale interactive web services and advanced AI applications make sophisticated decisions in real-time, based on executing a massive amount of computation tasks on thousands of servers. Task schedulers, which often operate in heterogeneous and volatile environments, require high throughput, i.e., scheduling millions of tasks per second, and low latency, i.e., incurring minimal scheduling delays for millisecond-level tasks. Scheduling is further complicated by other users' workloads in a shared system, other background activities, and the diverse hardware configurations inside datacenters. We present Rosella, a new self-driving, distributed approach for task scheduling in heterogeneous clusters. Rosella automatically learns the compute environment and adjusts its scheduling policy in real-time. The solution provides high throughput and low latency simultaneously because it runs in parallel on multiple machines with minimum coordination and only performs simple operations for each scheduling decision. Our learning module monitors total system load and uses the information to dynamically determine optimal estimation strategy for the backends' compute-power. Rosella generalizes power-of-two-choice algorithms to handle heterogeneous workers, reducing the max queue length of O(log n) obtained by prior algorithms to O(log log n). We evaluate Rosella with a variety of workloads on a 32-node AWS cluster. Experimental results show that Rosella significantly reduces task response time, and adapts to environment changes quickly.

关键词： automatically learns the compute environment distributed scheduler Heterogeneous Clusters high throughput

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GT-TSCH: Game-Theoretic distributed TSCH scheduler for Low-Power IoT Networks 43

GT-TSCH: Game-Theoretic Distributed TSCH Scheduler for Low-P...

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43rd IEEE International Conference on distributed Computing Systems (ICDCS)

作者： Tavallaie, Omid Zandavi, Seid Miad Haddadi, Hamed Zomaya, Albert Y. Univ Sydney Sch Comp Sci Sydney NSW Australia Broad Inst MIT & Harvard Cambridge MA 02142 USA Imperial Coll London London England

ISBN: (纸本)9798350339864

Time-Slotted Channel Hopping (TSCH) is a synchronous medium access mode of the IEEE 802.15.4e standard designed for providing low-latency and highly-reliable end-to-end communication. TSCH constructs a communication schedule by combining frequency channel hopping with Time Division Multiple Access (TDMA). In recent years, IETF designed several standards to define general mechanisms for the implementation of TSCH. However, the problem of updating the TSCH schedule according to the changes of the wireless link quality and node's traffic load left unresolved. In this paper, we use non-cooperative game theory to propose GT-TSCH, a distributed TSCH scheduler designed for low-power IoT applications. By considering selfish behavior of nodes in packet forwarding, GT-TSCH updates the TSCH schedule in a distributed approach with low control overhead by monitoring the queue length, the place of the node in the Directed Acyclic Graph (DAG) topology, the quality of the wireless link, and the data packet generation rate. We prove the existence and uniqueness of Nash equilibrium in our game model and we find the optimal number of TSCH Tx timeslots to update the TSCH slotframe. To examine the performance of our contribution, we implement GT-TSCH on Zolertia Firefly IoT motes and the Contiki-NG Operating System (OS). The evaluation results reveal that GT-TSCH improves performance in terms of throughput and end-to-end delay compared to the state-of-the-art method.

关键词： distributed scheduler Game Theory Internet of Things (IoT) Time Slotted Channel Hopping (TSCH)

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A Renewable Energy-Aware distributed Task scheduler for Multi-sensor IoT Networks

A Renewable Energy-Aware Distributed Task Scheduler for Mult...

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ACM SIGCOMM Workshop on Networked Sensing Systems for a Sustainable Society (NET4us)

作者： Liri, Elizabeth Ramakrishnan, K. K. Kar, Koushik Univ Calif Riverside Riverside CA 92521 USA Rensselaer Polytech Inst Troy NY USA

ISBN: (纸本)9781450393928

IoT devices are becoming increasingly complex, support multiple sensors, and often rely on batteries and renewable energy. Scheduling algorithms can help to manage their energy usage. When multiple devices cooperatively monitor an environment, scheduling sensing tasks across a distributed set of IoT devices can be challenging because they have limited information about other devices, limited energy, and communication bandwidth. In addition, sharing information between devices can be costly in terms of energy. Our Tier-based Task scheduling protocol (T2), is an energy-efficient distributed scheduler for a network of multi-sensor IoT devices. T2, adapting on an epoch-by-epoch basis distributes task executions throughout an epoch to minimize temporal sensing overlap without exceeding task deadlines. Our experiments show that T2 schedules an IoT device's sensing task start time before its deadline expires. When compared against a simple periodic scheduler, T2 schedules are closer to the optimal centralized EDF scheduler.

关键词： IoT distributed scheduler tier-based dynamic deadline-aware

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Sensing Together: Cooperative Task Adaptation and Scheduling for IoT-Nets using Renewable Energy 21

Sensing Together: Cooperative Task Adaptation and Scheduling...

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21st IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS)

作者： Liri, Elizabeth Ramakrishnan, K. K. Kar, Koushik Esposito, Flavio Univ Calif Riverside Dept Comp Sci & Engn Riverside CA 92521 USA Rensselaer Polytech Inst Elect Comp & Syst Engn Dept Troy NY USA St Louis Univ Comp Sci Dept St Louis MO 63103 USA

ISBN: (纸本)9798350363999;9798350364002

IoT devices used in various applications, such as monitoring agricultural soil moisture, or urban air quality assessment, are typically battery-operated and energy-constrained. We develop a lightweight and distributed cooperative sensing scheme that provides energy-efficient sensing of an area by reducing spatio-temporal overlaps in the coverage using a multi-sensor IoT network. Our "Sensing Together" solution includes two algorithms: distributed Task Adaptation (DTA) and distributed Block scheduler (DBS), which coordinate the sensing operations of the IoT network through information shared using a distributed "token passing" protocol. DTA adapts the sensing rates from their "raw" values (optimized for each IoT device independently) to minimize spatial redundancy in coverage, while ensuring that a desired coverage threshold is met at all points in the covered area. DBS then schedules task execution times across all IoT devices in a distributed manner to minimize temporal overlap. On-device evaluation shows a small token size and execution times of less than 0.6s on average while simulations show average energy savings of 5% per IoT device under various weather conditions. Moreover, when devices had more significant coverage overlaps, energy savings exceeded 30% thanks to cooperative sensing. In simulations of larger networks, energy savings range on average between 3.34% and 38.53%, depending on weather conditions. Our solutions consistently demonstrate near-optimal performance under various scenarios, showcasing their capability to efficiently reduce temporal overlap during sensing task scheduling.

关键词： multi-sensor IoT distributed scheduler energy efficiency task adaptation cooperative sensing comb placement problem

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Subutai: Speeding Up Legacy Parallel Applications Through Data Synchronization

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IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 2021年第5期32卷 1102-1116页

作者： Cataldo, Rodrigo Fernandes, Ramon Martin, Kevin J. M. Silveira, Jarbas Sanchez, Gustavo Sepulveda, Johanna Marcon, Cesar Diguet, Jean-Phillipe Pontificia Univ Catolica Rio Grande Sul PUCRS Sch Technol BR-90619900 Porto Alegre RS Brazil Pontificia Univ Catolica Rio Grande Sul PUCRS Fac Informat BR-90619900 Porto Alegre RS Brazil Univ Bretagne Sud UBS Lab STICC F-56100 Lorient France Univ Fed Ceara Dept Comp Sci Fortaleza Ceara Brazil Tech Univ Munich Lehrstuhl Sicherheit Informat Tech D-80333 Munich Germany UBS Univ CNRS Lab STICC F-56100 Lorient France

The decrease of the performance gain dictated by Moore's Law boosted the development of manycore architectures to replace single-core architectures. These new architectures must employ parallel applications and distribute its workload over a multitude of cores to reach the desired performance. Parallel applications are harder to develop than sequential ones since the developer must guarantee data integrity using synchronization primitives. While multiple novel solutions have been proposed to speed up parallel applications through handling one type of data synchronization primitive, exceptionally few works support multiple types of synchronization primitives and legacy code. This article proposes Subutai, a hardware/software co-design solution for accelerating multiple synchronization primitives without modifying the application source code. By providing a new user library, while retaining an existing synchronization API, legacy and novel applications can benefit from our solution. Our experimental evaluation, which provides a POSIX Threads implementation, demonstrates Subutai speeds up to 2.71x and 4.61x the execution of single- and multiple-application executions, respectively.

关键词： Synchronization Software Libraries Hardware Programming Optimization Computational modeling Legacy parallel applications PThreads network-on-chip distributed scheduler

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A handshake algorithm for scheduling communications in wireless sensor networks

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2022年第7期34卷

作者： Taktak, Emna Tounsi, Mohamed Mosbah, Mohamed Mnif, Abdessalem Hadj Kacem, Ahmed Univ Sfax ReDCAD Lab Sfax Tunisia Umm Al Qura Univ Mecca Saudi Arabia Univ Bordeaux CNRS LaBRI Bordeaux France

Wireless sensor networks (WSNs) are composed of sensors exchanging the information that they collect from the environment. The use of a scheduler offers an efficient solution to eliminate information redundancy and possible collisions in this network. A scheduler is responsible for choosing the sensors to exchange information at each step of the algorithm's execution. This article presents a WSN handshake algorithm (WSN-HS) scheduling the communications between every two sensors safely in an exclusive mode. Our WSN-HS is energy-efficient. It tries to elaborate communications between sensors with the minimum of messages and thus with the minimum of energy consumption. In addition, our algorithm is fault-tolerant to sensors' disappearance. Hence, when a sensor runs out of energy, the other sensors in the network will not be blocked and they will continue executing the distributed algorithm. We compare and evaluate our algorithm with another handshake algorithm. The results of the simulation done with two examples of distributed algorithms show that our algorithm significantly minimizes the energy consumption in the WSN. Moreover, in this article, we detail the analysis that emphasizes the efficiency of our WSN-HS algorithm.

关键词： distributed scheduler energy efficiency fault tolerance handshake algorithm wireless sensor network

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A distributed scheduler for air traffic flow management

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JOURNAL OF SCHEDULING 2012年第5期15卷 537-551页

作者： Landry, Steven J. Farley, Todd Ty Hoang Stein, Brian NASA Ames Res Ctr Moffett Field CA 94035 USA Methods Corp English Creek NJ USA

A system was developed to efficiently schedule aircraft into congested resources over long ranges and present that schedule as a decision support system. The scheduling system consists of a distributed network of independent schedulers, loosely coupled by sharing capacity information. This loose coupling insulates the schedules from uncertainty in long-distance estimations of arrival times, while allowing precise short-term schedules to be constructed. This "rate profile" mechanism allows feasible schedules to be produced over long ranges, essentially constructing precise short-range schedules that also ensure that future scheduling problems are solvable while meeting operational constraints. The system was tested operationally and demonstrated reduced airborne delay and improved coordination.

关键词： Air traffic flow management distributed scheduler Air traffic arrival scheduling Decision support

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A Reliable distributed Grid scheduler for Mixed Tasks

A Reliable Distributed Grid Scheduler for Mixed Tasks

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1st International Conference on Computer Science, Engineering and Information Technology (CCSEIT 2011)

作者： Kovvur, Ram Mohan Rao Ramachandram, S. Kadappa, Vijayakumar Govardhan, A. Vasavi Coll Engn Dept Comp Sci & Engn Hyderabad Andhra Pradesh India Osmania Univ Dept Comp Sci & Engn Hyderabad 500007 Andhra Pradesh India East West Inst Technol Dept MCA Bangalore Karnataka India JNTUH Dept Comp Sci & Engn Hyderabad Andhra Pradesh India

ISBN: (纸本)9783642240362;9783642240379

Scheduling of jobs is one of the crucial tasks in grid environment. We consider non-preemptive scheduling of mixed tasks in a computational grid. Recently, a general distributed scalable grid scheduler (GDS) was proposed. which prioritizes mission-critical tasks while maximizing the number of tasks meeting deadlines. However, the GDS scheduler did not consider the reliability factor, which may result in low successful schedule rates. In this paper, we propose a novel distributed grid scheduler which considers various parameters Priority, Deadline. CCR and reliability of grid nodes. The proposed scheduler maintains the tasks allocated to deficient grid nodes in a queue. Further the queued tasks are rescheduled to the other nodes of the grid. It is observed that RDGS-MT scheduler shows a significant improvement in terms of successfully scheduled tasks (hard, firm, soft) as compared to a GDS-S (GDS without shuffle phase). The results of our exhaustive simulation experiments demonstrate the superiority of the proposed scheduler over the GDS-S scheduler.

关键词： Grid Computing Scheduling Re-Scheduling distributed scheduler Reliability Priority Deadline

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Flex: Flexible and Energy Efficient Scheduling for Big Data Storage 44

Flex: Flexible and Energy Efficient Scheduling for Big Data ...

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44th Annual International Conference on Parallel Processing Workshops (ICPPW)

作者： Ma, Daokuan Wu, Yongwei Chen, Kang Zheng, Weimin Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China

ISBN: (纸本)9781467375894

Traditional distributed schedulers only consider the scheduling of jobs and treat the storage system as static and already deployed. However, individual application often needs its own configuration of storage system. Therefore, traditional distributed schedulers are not able to serve multiple tenants. To improve the resource utilization, some mechanisms are needed to consolidate multiple applications running on top of the same computing resources. Flex is such a system for helping the distributed scheduler to deploy a customized storage system before a job is scheduled without too much overhead incurred. The lightweight operating system level virtualization technology, aka containers in Linux, is used to wrap the computing environment and isolate different applications. Flex can achieve two goals that traditional distributed scheduler cannot provide. One is to deploy a specific storage system for the requirement of an individual application;the other is to consolidate applications for a better use of the underlying computing resources. Thus, by employing storage scheduling, Flex improves the resource utilization of distributed systems.

关键词： Containers Flexible printed circuits Hardware High performance computing Operating systems Virtual machining Virtualization Big Data distributed scheduler distributed System Linux Container Cache Memory System big data distributed Systems virtual machines Operating systems High Performance Computing Virtualization CONTAINERS Computer hardware Flexibility Resource utilization Flexible printed circuits virtual machining jobs

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