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The massive demand of mobile data traffic stimulates the emergence of cache-enabled heterogeneous cellular networks (HetNets). Caching at the network edge can reduce the duplicated transmissions of the contents and improve users' quality of service (QoS), however, the dense deployment of cache-enabled small base stations (SBSs) and relays poses a challenge on energy consumption. Several emerging technologies...
In order to achieve the goal of economic and environmental mutual optimization of micro-grid system operation, a general model of multi-objective dynamic optimal scheduling is established, which takes the independent system simulation module and the operation optimization module as the core. The simulation module uses energy model to evaluate economic and environmental indexes of the system scheduling...
As demands for cloud-based data processing continue to grow, cloud providers seek effective techniques that deliver value to the business without violating Service Level Agreements (SLAs). Cloud right-sizing has emerged as a very promising technique for making cloud services more cost-effective. In this paper, we present CRED, a novel framework for cloud right-sizing with execution deadlines and data...
The Software Defined Network (SDN) is a new networking paradigm, which separates the control plane and data plane. In this paper, we study two efficient large flow scheduling problems using SDN. We firstly present problem definitions, then we propose two algorithms based on Minimize-Cost Maximize-Flow (MCMF) model. One is for static model and the other for dynamic model. We show how to determine the...
In MapReduce model, the job execution time was prolonged by the straggler tasks in heterogeneity environments. The LATE scheduler has introduced the longest remaining time strategy, but it also has some drawbacks such as inaccurate estimated time and the wasting of system resources. In order to solve these problems, we propose two main algorithms : The parameter dynamic-tuning algorithm based history...
On the distributed or parallel heterogeneous computing systems, an application is usually decomposed into several independent and/or interdependent sets of cooperating subtasks and assigned to a set of available processors for execution. Heuristic-based task scheduling algorithms consist of the two typical phases of task prioritization and processor selection. However, heuristic-based task scheduling...
With the rapid advance of cloud computing, large scale data center plays a key role in cloud computing. Energy consumption of such distributed systems has become a prominent problem and received much attention. Among existing energy-saving methods, application scheduling can reduce energy consumption by replacing and consolidating applications to decrease the number of running servers. However, most...
Resource Scheduling is a centerpiece of data centers. However, most previous works concentrate only on one-dimensional model, which ignoring the fact that multiple resources such as CPU, memory and network bandwidth are consumed simultaneously. As cloud computing allows uncoordinated and heterogeneous users to share a data center, competition for multiple resources has become increasingly severe....
To solve high real-time and complexity calculation problems such as feature extraction and pattern classification when wireless sensor network real-time diagnosis and equipment health record of the mine coal underground equipments monitoring, this paper purpose a optimal algorithm for task scheduling underground wireless monitoring network based on distributed computing, this method use the fast convergence...
We study the problem of flow based scheduling in multi-hop wireless networks. And propose a Max Flows First-Shadow queue based Congestion Control (MFF-SCC) algorithm for combined scheduling and congestion control that aims to solve max-min fairness problem. We give out detailed analysis of the algorithm and also conduct simulations to verify its performance. The results of simulations indicate that...
Through the research to the 3D-parking scheduling, bring forward the use of GAAA algorithm to search for the shortest path with shortest time in parking scheduling firstly, the GAAAA algorithm inosculate the Genetic Algorithm (GA) and Ant Algorithm (AA), which make up the shortcoming of GA and AA very well. Furthermore, through the simulation analysis proved that GAAA have better performance than...
For solving the vehicle routing disruption problem which is caused by vehicles breakdown or traffic accidents in the logistic distribution system, an urgency vehicle scheduling scheme is established based on the theory of disruption management. According to the characteristics of the problem, Lagrangian relaxation approach is applied to simplify and divide the problem into two parts. The column generation...
Software as a Service (SaaS) is thriving as a new mode of service delivery and operation with the development of network technology and the maturity of application software. SaaS application providers offer services for multiple tenants through the ??single-instance multi-tenancy?? model, which can effectively reduce service costs due to scale effect. Meanwhile, the providers allocate resources according...
With the shortcoming of we can not search for the local optimum, this article has studied the problem of resource restricted and provided a kind of improved hereditary algorithm of adaptive immunity by the way of combining the adaptive operator of the hereditary algorithm of the immunity with the drawing dynamically of vaccine. According to the historical of searching information, the improved algorithm...
Task scheduling still remains one of the most challenging problems to achieve high performance in heterogeneous computing environments in spite of numerous efforts. This paper presents a novel scheduling algorithm based on learning classifier system for heterogeneous computing environment. In the presented algorithm, XCS classifier system is used to find the optimal task assignment on different processors,...
The rapid development of modern VLSI technology allows incorporating a complete system on a single chip using the system-on-chip (SoC) methodology. Test scheduling solution for SoC embedded IP cores is a very complex problem. It is necessary to test these cores in parallel for reducing test time. This paper presents an efficient approach based on particle swarm optimization (PSO) algorithm for the...
Non-traditional safety-critical systems are widely used in transportation control, banking and financial systems, and the management of water systems, which have different characteristics with traditional safety-critical systems. In those systems, tasks cannot be determined as critical or non-critical apparently but a few failures of some tasks are acceptable. This paper establishes a new schedule...
This paper proposes an Immune Particle Swarm Optimization (IPSO) algorithm and a model of grid task scheduling based on satisfaction rate that address multi-objective optimization problems of task scheduling in dynamic and heterogeneous grid environments. The IPSO algorithm is implemented in simulation environment of grid task scheduling according to the objective function based on satisfaction rate...
The data-intensive workflow in scientific and enterprise grids has gained popularity in recent times. Data-intensive workflow needs to access, process and transfer large datasets that may each be replicated on different data hosts. Because of the large data sets, the execution time is bounded by the cost of data transfer. Minimizing the time of transferring these datasets to the computational resources...
Cloud computing has gained popularity in recent times. As a cloud must provide services to many users at the same time and different users have different QoS requirements, the scheduling strategy should be developed for multiple workflows with different QoS requirements. In this paper, we introduce a multiple QoS constrained scheduling strategy of multi-workflows (MQMW) to address this problem. The...
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