On-off Scheduling Research Articles

Prototype Sistem Monitoring Lampu Penerangan Jalan Umum Menggunakan Zigbee dan Esp32

Street lighting, or Public Street Lighting (PJU), is crucial infrastructure in an area, particularly for nighttime traffic illumination. Efficiency and monitoring pose significant challenges in PJU management. Most PJUs lack a monitoring system, making control and malfunction detection difficult. Monitoring is expected to efficiently regulate the on-off schedule and detect malfunctions. This research aims to develop a cost-effective PJU monitoring and efficiency system without replacing many existing devices. The method employs Zigbee technology and Esp32. This system is anticipated to enhance efficiency and detect issues more promptly than before.

Using Facebook, Instagram, and Pinterest advertising campaigns to increase enrollment in newborn screening research

IntroductionSocial media ad campaigns can be an efficient, cost-effective way to recruit for studies online, especially as the onset of the COVID-19 pandemic limited in-person recruitment. Early Check, a large ongoing study offering testing for a panel of conditions for all newborns in North Carolina, uses social media ad campaigns, along with direct mail, email, print materials in health care settings, and messages through patient portals to contact pregnant women and mothers with eligible newborns. All materials refer women to the online Early Check portal for consent and enrollment in the study.MethodsTo evaluate social media options for outreach and recruitment, we ran two paid ad campaigns on Pinterest in May and July 2021 and compared performance to simultaneous Facebook and Instagram campaigns.ResultsFacebook and Instagram cost $136.53 per sign-up in May and July. Our first Pinterest campaign in May resulted in 206,416 impressions, 529 link clicks, and a cost per sign-up of $536.56. After adjusting the campaign to incorporate lessons learned about the platform, the second Pinterest campaign in July resulted in 225,286 impressions, 621 link clicks, and a cost per sign-up of $216.55.DiscussionOthers looking to implement social media ad campaigns for public health recruitment should note that ad costs have increased since 2020. However, social media ad campaigns on Facebook, Instagram, and Pinterest remain a cost-effective and convenient way to recruit participants for studies, especially when in-person efforts are not feasible. Ad campaign strategy should also be tailored to the specific platform. Facebook and Instagram ads should be run together in the same campaign to optimize the budget across both platforms and should run using an on-off schedule. Pinterest campaigns should run for a longer period to optimize continually for sign-ups over time.

Peak load minimization in smart grid by optimal coordinated ON–OFF scheduling of air conditioning compressors

We address the problem of minimizing the peak load by optimal coordinated ON–OFF scheduling of the compressors of air conditioners (ACs) connected in a smart grid. For this purpose, we consider a simplified model of power consumption profile, i.e., on-time and off-time durations and power consumption values of a split type AC. We model the necessary constraints and formulate an optimization problem to minimize the peak load by optimal coordinated ON–OFF scheduling of the AC compressors. The optimization problem is found to be a complex mixed integer linear programming problem. We optimally solve the problem for a small number of ACs by using an optimization tool. Unfortunately, due to the computational complexity, the tool cannot solve the problem for a large number of ACs. For a large number of ACs, we develop a heuristic algorithm to solve the problem. Using the optimization tool and the heuristic algorithm, we determine the peak load, load variance, and energy consumption in operating a number of ACs and compare them with the results obtained for a traditional non-coordinated AC operation. We find that both the optimal and heuristic solution approaches significantly reduce the peak load and load variance with some increment of energy consumption. Further, the computation time of the scheduling of the AC compressors of an air conditioning system under the heuristic algorithm is found to be significantly less compared to the time bound on scheduling computation of the AC compressors even when the number of ACs in the system is large.

On-Off Scheduling for Electric Vehicle Charging in Two-Links Charging Stations Using Binary Optimization Approaches.

In this study, we deal with the problem of scheduling charging periods of electrical vehicles (EVs) to satisfy the users’ demands for energy consumption as well as to optimally utilize the available power. We assume three-phase EV charging stations, each equipped with two charging ports (links) that can serve up to two EVs in the scheduling period but not simultaneously. Considering such a specification, we propose an on–off scheduling scheme wherein control over an energy flow is achieved by flexibly switching the ports in each station on and off in a manner such as to satisfy the energy demand of each EV, flatten the high energy-consuming load on the whole farm, and to minimize the number of switching operations. To satisfy these needs, the on–off scheduling scheme is formulated in terms of a binary linear programming problem, which is then extended to a quadratic version to incorporate the smoothness constraints. Various algorithmic approaches are used for solving a binary quadratic programming problem, including the Frank–Wolfe algorithm and successive linear approximations. The numerical simulations demonstrate that the latter is scalable, efficient, and flexible in a charging procedure, and it shaves the load peak while maintaining smooth charging profiles.

Load-Based On/Off Scheduling for Energy-Efficient Delay-Tolerant 5G Networks

Dense deployment of small cells is seen as one of the major approaches for addressing the traffic demands in next-generation 5G wireless networks. The energy efficiency, however, becomes a concern along with the deployment of massive amount of small cells. In this paper, we consider the energy-efficient small cell networks (SCNs) using smart on/off scheduling (OOS) strategies, where a certain fraction of small base stations (SBSs) are put into less energy-consuming sleeping states to save energy. To this end, we first represent the overall SCN traffic by a new load variable, and analyze its statistics rigorously using Gamma approximation. We then propose two novel OOS algorithms exploiting this load variable in centralized and distributed fashions. We show that proposed load-based OOS algorithms can lead to as high as 50% of energy savings without sacrificing the average SCN throughput. In addition, load-based strategies are shown to work well under high SCN traffic and delay-intolerant circumstances, and can be implemented efficiently using the load statistics. We also show that the performance of load-based algorithms gets maximized for certain length of sleeping periods, where assuming short sleep periods is as energy-inefficient as keeping SBSs in sleep states for very long.

On-off scheduling schemes for power-constrained electric vehicle charging

In this paper, we study the problem of establishing a dynamic charging schedule of electric vehicles (EVs) at a charging station, assuming that limited power implies that only a limited number of EVs can charge simultaneously. The only control we assume to be available to the charging station is the ability to (at any given time) turn on or off the power supply to any EV, with this tool we want to develop a charging schedule that will satisfy the energy demands of the EVs in their intended deadlines. We propose two distinct approaches to this problem: a discretized time version, based on a greedy-like algorithm, and a continuous time version, based on linear programming. We compare these two approaches and numerically study the improvement they yield in the efficiency of the charging procedure, when applied to simulated data based on real parking data. Finally, we illustrate the flexibility of the models by sketching several possible extensions.

Energy Efficient Smart Sensor Network Routing Protocol using Node Scheduling

needs are going more technology dependent in last decade. Technology touches live everywhere and also reach the area where humans unable to reach. One of Such important application is Wireless Sensor Networks (WSNs). This helps to collect data from different conditions where human faces challenges to gather information about atmosphere or environment. Apart of its advantage, WSN suffer from many different challenges like limited sensor node electric capacity, pattern of node deployment, data sending mechanism etc. To manage WSN with optimum resource utilization various data transmission methods have been given in recent years. This paper proposed another better method for improving network life span and increase stability of WSN. Proposed method manages all sensor nodes energy power within intelligence manor by using ON-OFF scheduling of node data transmission. Few nodes in ON state sense data and send to base station for one round of data transmission while other nodes are in power saving OFF mode by doing nothing neither sense nor transmit data. But for next round nodes are in ON status nodes goes to OFF power saving modes to save power and OFF mode nodes sense and send data to base station. This method is compared with other technique using same parameter while simulation and proposed method outperform better in all aspects of WSN comparison. Keywordsefficient, Data transmission protocol, ON mode, OFF mode, WSN, scheduling

Maximum lifetime suspect monitoring on the street with battery-powered camera sensors

A camera sensor network is a sensor network of a group of camera sensors and is being deployed for various surveillance and monitoring applications. In this paper, we propose a new surveillance model for camera sensor network, namely half-view model, which requires a camera sensor network to capture the face image of any object if it moves forward to pass over an area of interest. Based on this new surveillance model, we introduce a new sleep-wakeup scheduling problem in camera sensor network, namely the maximum lifetime half-view barrier-coverage (MaxL-HV-BC) problem, whose goal is to find an on-off schedule of battery-operated camera sensors such that the continuous time duration providing half-view barrier-coverage over an area of interest is maximized. We develop a strategy to check if a region is half-view covered by a given set of camera sensors, and use this strategy to design two new heuristic algorithms for MaxL-HV-BC. We also conduct simulations to compare the average performance of the proposed algorithms with a trivial solution as well as the theoretical upper bound.

Delay Behavior of On-Off Scheduling: Extending Idle Periods

On-off scheduling of systems that have the ability to sleep can be used to extend system idle periods and enable greater opportunities for energy savings from sleeping. In this paper, we achieve a theoretical understanding of the delay behavior of on-off scheduling as it may apply to communications links and other systems capable of sleeping. We consider a single-server coalescing queue with a scheduler that schedules on-off periods for the server in order to extend idle periods of the downstream link. At the start of an off period (duration To f f ) the server stops serving jobs immediately if idle, or after processing a job already in service. Service of any queued and arriving jobs begins at the start of the next on period (duration Ton). On and off periods are fixed. We solve for the scheduling queue behavior as a function of To f f , Ton, interarrival time t, service time x, and time of first arrival g for periodic job arrivals. Our results are closed form and have both theoretical and pr actical significance.

Distributed Rate Allocation for Wireless Networks

This paper develops a distributed algorithm for rate allocation in wireless networks that achieves the same throughput region as optimal centralized algorithms. This cross-layer algorithm jointly performs medium access control and physical-layer rate adaptation. The paper establishes that this algorithm is throughput-optimal for general rate regions. In contrast to on-off scheduling, rate allocation enables optimal utilization of physical-layer schemes by scheduling multiple rate levels. The algorithm is based on local queue-length information, and thus the algorithm is of significant practical value. An important application of this algorithm is in multiple-band multiple-radio throughput-optimal distributed scheduling for white-space networks. The algorithm requires that each link can determine the global feasibility of increasing its current data-rate. In many classes of networks, any one link's data-rate primarily impacts its neighbors and this impact decays with distance. Hence, local exchanges can provide the information needed to determine feasibility. Along these lines, the paper discusses the potential use of existing physical-layer control messages to determine feasibility. This can be considered as a technique analogous to carrier sensing in carrier sense multiple access (CSMA) networks.

An Energy-Aware Scheduling Scheme for Wireless Sensor Networks

Wireless sensor networks are widely adopted in target tracking applications. Wireless sensor nodes are battery-powered devices. These low-cost communication devices have high failure rates and are vulnerable to attacks. To maintain network connectivity and to ensure large network coverage, excessive wireless sensor nodes are usually deployed to provide redundancy. However, these extra wireless sensor nodes would dissipate more power. This problem can be relieved by proper scheduling and putting unnecessary sensor nodes into sleep mode. In this paper, an energy-aware scheduling scheme for wireless sensor networks is proposed. The proposed scheme is a kind of an adaptive/periodic on-off scheduling scheme in which sensor nodes use only local information to make scheduling decisions. The scheme is evaluated in terms of target hit rate, detection delay, and energy consumption per successful target detection. Simulation results show that when comparing with other generic scheduling schemes, the proposed scheme can significantly reduce energy consumption.

S-MAPEL: Monotonic optimization for non-convex joint power control and scheduling problems

In interference-limited wireless networks where simultaneous transmissions on nearby links heavily interfere with each other, power control alone is not sufficient to eliminate strong levels of interference between close-by links. In this case, scheduling, which allows close-by links to take turns to be active, plays a crucial rule for achieving high system performance. Joint power control and scheduling that maximizes the system utility has long been a challenging problem. The complicated coupling between the signal-to-interference ratio of concurrently active links as well as the flexibility to vary power allocation over time gives rise to a series of non-convex optimization problems, for which the global optimal solution is hard to obtain. This paper is a first attempt to solve the non-convex joint power control and scheduling problems efficiently in a global optimal manner. In particular, it is the monotonicity rather than the convexity of the problem that we exploit to devise an efficient algorithm, referred to as S-MAPEL, to obtain the global optimal solution. To further reduce the complexity, we propose an accelerated algorithm, referred to as A-S-MAPEL, based on the inherent symmetry of the optimal solution. The optimal joint-power-control-and-scheduling solution obtained by the proposed algorithms serves as a useful benchmark for evaluating other existing schemes. With the help of this benchmark, we find that on-off scheduling is of much practical value in terms of system utility maximization if off-the-shelf wireless devices are to be used.

Capacities of Physical Layer Scheduling Strategies on a Shared Link

We compare capacities of three physical layer scheduling algorithms: on-off scheduling (OOS), maximum SNR, and round robin schedulers. With OOS, downlink transmission is suspended if the instantaneous received SNR in the mobile station falls below a given threshold requiring only one feedback bit per user, which considerably decreases the overhead of the feedback signaling when compared with maximum SNR scheduler. In case of FDD systems, OOS and maximum SNR schedulers require a fast feedback channel from mobile to base station like the one in the FDD WCDMA system, while round robin operates independently of the channel state.

The Effect of On-Off Scheduling to the Required Transmit Power in Systems with Fast Power Control

Physical layer channel-aware scheduling may significantly improve coverage and throughput of IP based services in wireless cellular networks, and the feasibility of such schedulers is actively studied within 3G and 4G systems. A channel-aware scheduler requires access to instantaneous channel state information in order to direct transmission to users with favorable channel conditions. In frequency division duplex (FDD) systems, this requires a fast feedback channel between mobile and base stations, and the overhead of the feedback control channel should be kept as low as possible. In this paper, we study the effect of control channel overhead to on-off scheduling (OOS) when fast transmit power control is applied in data and control channels. On-off scheduling is a simple channel-aware scheduling algorithm, where transmission to a user is suspended if the transmit power exceeds a given threshold. On-off scheduling is applied on the data channel while control channel is always on so that the scheduler is able to obtain channel state information from active users. The gain of OOS strongly depends on the power ratio between control and data channels, and increased interference due to control signaling and decreased interference due to channel-aware scheduling should be jointly considered in system design. Gains in the required transmit power are translated into gains in coverage and capacity assuming WCDMA parameters, and the results can be applied, e.g., when designing scheduling algorithms and corresponding signaling formats for WCDMA uplink.