Distributed Scheduling Algorithm Research Articles

Bidirectional Energy Trading and Residential Load Scheduling with Electric Vehicles in the Smart Grid

Electric vehicles (EVs) will play an important role in the future smart grid because of their capabilities of storing electrical energy in their batteries during off-peak hours and supplying the stored energy to the power grid during peak hours. In this paper, we consider a power system with an aggregator and multiple customers with EVs and propose novel electricity load scheduling algorithms which, unlike previous works, jointly consider the load scheduling for appliances and the energy trading using EVs. Specifically, we allow customers to determine how much energy to purchase from or to sell to the aggregator while taking into consideration the load demands of their residential appliances and the associated electricity bill. We propose two different approaches: a collaborative and a non-collaborative approach. In the collaborative approach, we develop an optimal distributed load scheduling algorithm that maximizes the social welfare of the power system. In the non-collaborative approach, we model the energy scheduling problem as a non-cooperative game among self-interested customers, where each customer determines its own load scheduling and energy trading to maximize its own profit. In order to resolve the unfairness between heavy and light customers in the non-collaborative approach, we propose a tiered billing scheme that can control the electricity rates for customers according to their different energy consumption levels. In both approaches, we also consider the uncertainty in the load demands, with which customers' actual energy consumption may vary from the scheduled energy consumption. To study the impact of the uncertainty, we use the worst-case-uncertainty approach and develop distributed load scheduling algorithms that provide the guaranteed minimum performances in uncertain environments. Subsequently, we show when energy trading leads to an increase in the social welfare and we determine what are the customers' incentives to participate in the energy trading in various usage scenarios including practical environments with uncertain load demands.

DSS: Distributed SINR-Based Scheduling Algorithm for Multihop Wireless Networks

The problem of developing distributed scheduling algorithms for high throughput in multihop wireless networks has been extensively studied in recent years. The design of a distributed low-complexity scheduling algorithm becomes even more challenging when taking into account a physical interference model, which requires the SINR at a receiver to be checked when making scheduling decisions. To do so, we need to check whether a transmission failure is caused by interference due to simultaneous transmissions from distant nodes. In this paper, we propose a scheduling algorithm under a physical interference model, which is amenable to distributed implementation with 802.11 CSMA technologies. The proposed scheduling algorithm is shown to achieve throughput optimality. We present two variations of the algorithm to enhance the delay performance and to reduce the control overhead, respectively, while retaining throughput optimality.

Simultaneous RTS and Sequential CTS Considering Multiple Cooperative Relays

We propose a distributed scheduling algorithm for wireless ad hoc systems that use cooperative transmission in which multiple cooperative relays can transmit at the same time by using an amplify-and-forward (AF) scheme or a decode-and-forward (DF) scheme. Our proposed scheme is a carrier-sense-multiple-access-like (CSMA-like) scheduling algorithm, which uses simultaneous request-to-send (RTS) and sequential clear-to-send (CTS) (SRSC) transmission in which multiple transmitters broadcast RTS at the same time, and the power of CTS transmission changes dynamically according to the relaying scheme used and the number of cooperative relays. Therefore, each cooperative transmission set can recognize efficiently whether its transmission will interfere with neighboring ongoing transmissions. Through performance evaluation by simulation, we show that the proposed scheme can enhance the performance of wireless ad hoc systems that use cooperative transmission.

Distributed CSMA Algorithms for Link Scheduling in Multihop MIMO Networks Under SINR Model

In this paper, we study distributed scheduling in multihop multiple-input-multiple-output (MIMO) networks. We first develop a model that provides the upper layers a set of rates and signal-to-interference-plus-noise ratio (SINR) requirements that capture the rate-reliability tradeoff in MIMO communications. The main thrust of this paper is then dedicated to developing distributed carrier sense multiple access (CSMA) algorithms for MIMO-pipe scheduling under the SINR interference model. We choose the SINR model over the extensively studied protocol-based interference models because it more naturally captures the impact of interference in wireless networks. The coupling among the links caused by the interference under the SINR model makes the problem of devising distributed scheduling algorithms very challenging. To that end, we explore the CSMA algorithms for MIMO-pipe scheduling from two perspectives. We start with an idealized continuous-time CSMA network, where control messages can be exchanged in a collision-free manner, and devise a CSMA-based link scheduling algorithm that can achieve throughput optimality under the SINR model. Next, we consider a discrete-time CSMA network, where the message exchanges suffer from collisions. For this more challenging case, we develop a scheduling algorithm by imposing a more stringent SINR constraint on the MIMO-pipe model. We show that the proposed conservative scheduling achieves an efficiency ratio bounded from below.

Distributed feedback control algorithm in an auction-based manufacturing planning and control system

In today's manufacturing enterprise, customer service performance is highly dependent on the effectiveness of the company's manufacturing planning and control system (MPCS). Most of the current MPCSs that employ the centralised planning approach can have drawbacks, such as structural rigidity, difficulty in designing a control system, and lack of flexibility. An auction-based manufacturing planning and control system (AMPCS) allows negotiation-based decision making, however, the distributed scheduling algorithm usually attempts to achieve only its objective without considering the global objective, and a contradiction problem might occur between the local objective and the overall system performance. Therefore, the objective of this research is to develop a distributed scheduling algorithm called a closed-loop feedback simulation (CLFS) approach for an AMPCS which includes adaptive control of the auction-based bidding sequence to prevent the first bid first serve rule and may dynamically allocate production resources to operations. CLFS iteratively adjusts the bidding sequence using the deviation between the predicted completion time and the due date to improve the scheduling performance. The results obtained from the computational experiments show that the proposed CLFS algorithm can obviously improve production performance compared to previous studies.

Exploiting Cooperative Relay for High Performance Communications in MIMO Ad Hoc Networks

With the popularity of wireless devices and the increase of computing and storage resources, there are increasing interests in supporting mobile computing techniques. Particularly, ad hoc networks can potentially connect different wireless devices to enable more powerful wireless applications and mobile computing capabilities. To meet the ever increasing communication need, it is important to improve the network throughput while guaranteeing transmission reliability. Multiple-input-multiple-output (MIMO) technology can provide significantly higher data rate in ad hoc networks where nodes are equipped with multiantenna arrays. Although MIMO technique itself can support diversity transmission when channel condition degrades, the use of diversity transmission often compromises the multiplexing gain and is also not enough to deal with extremely weak channel. Instead, in this work, we exploit the use of cooperative relay transmission (which is often used in a single antenna environment to improve reliability) in a MIMO-based ad hoc network to cope with harsh channel condition. We design both centralized and distributed scheduling algorithms to support adaptive use of cooperative relay transmission when the direct transmission cannot be successfully performed. Our algorithm effectively exploits the cooperative multiplexing gain and cooperative diversity gain to achieve higher data rate and higher reliability under various channel conditions. Our scheduling scheme can efficiently invoke relay transmission without introducing significant signaling overhead as conventional relay schemes, and seamlessly integrate relay transmission with multiplexed MIMO transmission. We also design a MAC protocol to implement the distributed algorithm. Our performance results demonstrate that the use of cooperative relay in a MIMO framework could bring in a significant throughput improvement in all the scenarios studied, with the variation of node density, link failure ratio, packet arrival rate, and retransmission threshold.

Real-Time Opportunistic Scheduling for Residential Demand Response

Demand response is a key feature of the smart grid. The addition of bidirectional communication to today's power grid can provide real-time pricing (RTP) to customers via smart meters. A growing number of appliance companies have started to design and produce smart appliances which embed intelligent control modules to implement residential demand response based on RTP. However, most of the current residential load scheduling schemes are centralized and based on either day-ahead pricing (DAP) or predicted price, which can deviate significantly from the RTP. In this paper, we propose an opportunistic scheduling scheme based on the optimal stopping rule as a real-time distributed scheduling algorithm for smart appliances' automation control. It determines the best time for appliances' operation to balance electricity bill reduction and inconvenience resulting from the operation delay. It is shown that our scheme is a distributed threshold policy when no constraint is considered. When a total power constraint exists, the proposed scheduling algorithm can be implemented in either a centralized or distributed fashion. Our scheme has low complexity and can be easily implemented. Simulation results validate proposed scheduling scheme shifts the operation to off-peak times and consequently leads to significant electricity bill saving with reasonable waiting time.

Downlink Scheduling with Transmission Strategy Selection for Multi-Cell MIMO Systems

In this paper, we study downlink scheduling with transmission strategy selection in multi-cell multiple-input multiple-output (MIMO) systems. Depending on the level of inter-cell interference experienced by a user, the scheduler can choose between two MIMO transmission strategies, namely, spatial multiplexing and interference alignment. We formulate an optimization problem which aims to jointly select a user and the corresponding transmission strategy for each base station in order to maximize the overall system utility while stabilizing all transmission queues. We first develop a centralized dynamic scheduling scheme with transmission strategy selection by using a stochastic network optimization approach. To reduce the communication overhead, we then propose a distributed scheduling algorithm which only requires limited message exchange between the base stations. We also consider the impact of imperfect channel state information on the scheduling schemes and propose an efficient rate adjustment method to improve the performance for this case. Simulation results show that the performance of the proposed distributed scheduling scheme is close to that of the centralized scheduling scheme, and both schemes achieve a better performance than schemes employing a single transmission strategy.

Implementation of Tree Based Itinerary Design (TBID) Algorithm Over Wireless Sensor networks by Using Mobile Agent

In many sensor network applications viz., environmental monitoring, spatial exploration and battlefield surveillance, sensed data is aggregated and transmitted to the sinks for analysis. Thus, in- network data aggregation (2) becomes an important technique in wireless sensor networks and has been well studied in recent years. In general, any sensory network suffers with two problems i.e., i) the time latencies of the existing scheduling algorithms are still high, and ii) the other one is that all the existing algorithms are centralized, which are inherently inefficient. Hence, in this paper, we present a distributed scheduling algorithm generating collision-free schedules with latency bound, based on TBID, which employs multiple Mobile Agents (MAs) for completing the aggregation task on WSNs. The algorithm not only determines the proper number of MAs for minimizing the total aggregation cost but also constructs low-cost itineraries for each of them. In this paper, we adopt TBID that improves upon NOID by following a more direct approach to the problem of determining low-cost MA itineraries. Specifically, based on an accurate formula for the total energy expended during MA migration, we follow a greedy- like approach for distributing SNs in multiple MA itineraries, and algorithm determines a spanning forest of trees in the network, calculates efficient tree traversal orders (itineraries), and eventually, assigns these itineraries to individual MAs.) Keywords-component; TBID(Tree Based Itinerary Design) ,wireless sensor networks, data aggregation, mobile agents

Proposal and Evaluation of Load-Dependent Distributed Scheduling Algorithm for WiMAX in Mesh Mode

The IEEE 802.16 standard defines a broadband access network technology called WiMAX, that besides the point-to-multipoint mode it also defines a mesh mode. In this paper we propose a modification of scheduling defined in the standard for the mesh mode to incorporate dependence on the node's load. The performance of the load-dependent distributed scheduling is compared with the distributed scheduling and the centralized scheduling of the standard, using NS-2 simulator with a modified WiMAX module. According to the simulations results, the load-dependent distributed scheduling algorithm outperformed the standard distributed algorithm in terms of the evaluated metrics.

COORDINATED DISTRIBUTED SCHEDULING IN WIRELESS MESH NETWORK

IEEE 802.16 based wireless mesh networks (WMNs) are a promising broadband access solution to support flexibility, cost effectiveness and fast deployment of the fourth generation infrastructure based wireless networks. Reducing the time for channel establishment is critical for low latency/interactive Applications. According to IEEE 802.16 MAC protocol, there are three scheduling algorithms for assigning TDMA slots to each network node: centralized and distributed the distributed is further divided into two operational modes coordinated distributed and uncoordinated distributed. In coordinated distributed scheduling algorithm, network nodes have to transmit scheduling message in order to inform other nodes about their transfer schedule. In this paper a new approach is proposed to improve coordinated distributed scheduling efficiency in IEEE 802.16 mesh mode, with respect to three parameter Throughput, Average end to end delay and Normalized Overhead. For evaluating the proposed networks efficiency, several extensive simulations are performed in various network configurations and the most important system parameters which affect the network performance are analyzed

Optimization-Based Design of Wireless Link Scheduling With Physical Interference Model

We address the link-scheduling problem in wireless multihop networks under the realistic physical interference model. Different from most works, which adopt the protocol interference model that treats the pairwise interference, we use the physical interference model to reflect the aggregated signal-to-interference-plus-noise ratio (SINR), which is a more accurate abstraction of the real scenarios. We first propose a centralized scheduling method based on the integer linear programming (ILP) and get an approximate solution by relaxing it to linear programming (LP). The probability bound of getting the guaranteed approximate factor is given, which is distinguished from other LP-based algorithms. Then, for the cases where the required global information is hard to get, a distributed scheduling algorithm is proposed. We simplify the formulation of the scheduling problem in the distributed scenarios and calculate the optimal solution as the transmission probability. This method can be implemented on each node through the Jacobi algorithm, only relying on local channel information. Simulation results show that it converges fast to the optimal solution and provides good throughput performance comparable with the centralized algorithm.

Maximal Scheduling in Wireless Networks with Priorities

We consider a general class of low complexity distributed scheduling algorithms in wireless networks, prioritized maximal scheduling, which compute a maximal set of transmitting links in each time slot according to certain pre-specified static priorities. The proposed scheduling scheme has low complexity, and is easily amendable for distributed implementation, such as adjusting inter-frame space (IFS) parameters under the ubiquitous 802.11 protocols. We provide throughput guarantees on the proposed scheduling scheme, by proving tight lower bound on the stability region and scheduling efficiency associated with a fixed priority vector. We next propose an online low complexity priority assignment algorithm, which can stabilize any arrival rate that is in the union of the lower bound regions of all priorities. The throughput guarantees are proved by fluid limits, and therefore can be applied to very general stochastic arrival processes. Finally, the performance of the proposed prioritized maximal scheduling scheme is verified by simulation results.

Stability and delay of distributed scheduling algorithms for networks of conflicting queues

This paper explains recent results on distributed algorithms for networks of conflicting queues. At any given time, only specific subsets of queues can be served simultaneously. The challenge is to select the subsets in a distributed way to stabilize the queues whenever the arrival rates are feasible. One key idea is to formulate the subset selection as an optimization problem where the objective function includes the entropy of the distribution of the selected subsets. The dual algorithm for solving this optimization problem provides a distributed scheduling algorithm that requires only local queue-length information. The algorithm is based on the CSMA (Carrier Sense Multiple Access) protocol in wireless networks. We also explain recent results, some of them unpublished so far, on the delay properties of these algorithms. In particular, we present a framework for queuing stability under bounded CSMA parameters, and show how the expected queue lengths depend on the throughput region to be supported. When the arrival rates are within a fraction of the capacity region, queue lengths that are polynomial (or even logarithmic) in the number of queues can be achieved.

Maximal Scheduling in Wireless Ad Hoc Networks With Hypergraph Interference Models

This paper proposes a hypergraph interference model for the scheduling problem in wireless ad hoc networks. The proposed hypergraph model can take the sum interference into account and, therefore, is more accurate as compared with the traditional binary graph model. Further, different from the global signal-to-interference-plus-noise ratio (SINR) model, the hypergraph model preserves a localized graph-theoretic structure and, therefore, allows the existing graph-based efficient scheduling algorithms to be extended to the cumulative interference case. Finally, by adjusting certain parameters, the hypergraph can achieve a systematic tradeoff between the interference approximation accuracy and the user node coordination complexity during scheduling. As an application of the hypergraph model, we consider the performance of a simple distributed scheduling algorithm, i.e., maximal scheduling, in wireless networks. We propose a lower bound stability region for any maximal scheduler and show that it achieves a fixed fraction of the optimal stability region, which depends on the interference degree of the underlying hypergraph. We also demonstrate the interference approximation accuracy of hypergraphs in random networks and show that hypergraphs with small hyperedge sizes can model the interference quite accurately. Finally, the analytical performance is verified by simulation results.

Cluster based node scheduling method for wireless sensor networks

By researching on the node scheduling problem of m-covered and connected sensor networks, a new concept of two-hops-cluster is proposed in this paper, and based on it, a new distributed node scheduling algorithm THCNS for allocating all nodes in the sensor network into k(k m) different groups {0, 1,...,k− 1} is designed, without requiring location information. Our algorithm guarantees that each group to be connected and maintains the coverage ratio with high possibility. Theoretical analysis and simulation results show that it has better performance than previous randomized scheduling scheme, and can prolong the lifetime of the sensor network effectively.

Link establishment and performance evaluation in IEEE 802.16 wireless mesh networks

Wireless mesh networks (WMNs) are one of the emerging technologies. Their capability for self-organization significantly reduces the complexity of network deployment and maintenance, and thus, requires minimal upfront investment. These networks consist of simple mesh routers and mesh clients, where mesh routers have minimal mobility and form the backbone of WMNs. They provide network access for both mesh and conventional clients. IEEE 802.16 standard (www.ieee 802.org/16) is a recent standard for broadband wireless access networks, which includes a mesh mode operation for distributed channel access of peering nodes. In accordance with the IEEE 802.16 MAC protocol, time is partitioned into frames of fixed duration, each one divided into two sub-frames, for control and data transmission, respectively. Slots in the control sub-frame are used by nodes to negotiate the schedule of transmissions in data sub-frames, and are accessed by means of a collision-free distributed procedure, namely the mesh election procedure. In this paper, we have analyzed the performance of the mesh election procedure by means of simulations, and identify the system configuration parameters that have the most impact on the performance of control message transmission using distributed scheduling algorithm.

Multi-agent-based proactive–reactive scheduling for a job shop

Multi-agent-based proactive–reactive scheduling for job shops is presented, aiming to hedge against the uncertainties of dynamic manufacturing environments. This scheduling mechanism consists of two stages, including proactive scheduling stage and reactive scheduling stage. In the proactive scheduling stage, the objective is to generate a robust predictive schedule against known uncertainties; in the reactive scheduling stage, the objective is to dynamically rectify the predictive schedule to adapt to unknown uncertainties, viz. the reactive scheduling stage is actually complementary to the proactive scheduling stage. A stochastic model is presented, which concerns uncertain processing times in proactive scheduling stage on the basis of analyzing the deficiencies of a classical scheduling model for a production schedule in practice. For the stochastic scheduling problem, a multi-agent-based architecture is proposed and a distributed scheduling algorithm is used to solve this stochastic problem. Finally, the repair strategies are introduced to maintain the original proactive schedule when unexpected events occur. Case study examples show that this scheduling mechanism generates more robust schedules than the classical scheduling mechanism.

Performance driven distributed scheduling of parallel hybrid computations

Exascale computing is fast becoming a mainstream research area. In order to realize exascale performance, it is necessary to have efficient scheduling of large parallel computations with scalable performance on a large number of cores/processors. The scheduler needs to execute in a pure distributed and online fashion, should follow affinity inherent in the computation and must have low time and message complexity. Further, it should also avoid physical deadlocks due to bounded resources including space/memory per core. Simultaneous consideration of these factors makes affinity driven distributed scheduling particularly challenging. We attempt to address this challenge for hybrid parallel computations which contain tasks that have pre-specified affinity to a place and also tasks that can be mapped to any place in the system. Specifically, we address two scheduling problems of the type P m | M j , p r e c | C max . This paper presents online distributed scheduling algorithms for hybrid parallel computations assuming both unconstrained and bounded space per place. We also present the time and message complexity for distributed scheduling of hybrid computations. To the best of our knowledge, this is the first time that distributed scheduling algorithms for hybrid parallel computations have been presented and analyzed for time and message bounds under both unconstrained space and bounded space.

Distributed Task Scheduling Subject To Arbitrary Constraints

AbstractThis paper presents a distributed scheduling problem and a distributed algorithm to solve it. The problem is motivated by military missions where tasks are assigned to various vehicles and tasks must be scheduled to satisfy constraints between them. The distributed scheduling algorithm is capable of finding a solution in the presence of arbitrary scheduling constraints, e.g., logical or temporal constraints. These types of missions present the challenge of planning using computer systems that are distributed in the sense of information and authority. This motivates the development of distributed planning algorithms that can overcome these challenges. The distributed scheduling algorithm used here is demonstrated on an example involving two unmanned air vehicles and two unmanned ground vehicles and is shown to be correct and complete.