Utilizing priority-based packet scheduling based on preemptive priority scheduling in wireless sensor networks

Scheduling different types of packets, such as realtime and non-real-time data packets, at sensor nodes with resource constraints in Wireless Sensor Networks (WSN) is of vital importance to reduce sensors' energy consumptions and end-to-end data transmission delays. Most of the existing packet-scheduling mechanisms of WSN use First Come First Served (FCFS), non-preemptive priority and preemptive priority scheduling algorithms. These algorithms incur a high processing overhead and long end-to-end data transmission delay due to the FCFS concept, starvation of high priority real-time data packets due to the transmission of a large data packet in nonpreemptive priority scheduling, starvation of non-real-time data packets due to the probable continuous arrival of real-time data in preemptive priority scheduling, and improper allocation of data packets to queues in multilevel queue scheduling algorithms. Moreover, these algorithms are not dynamic to the changing requirements of WSN applications since their scheduling policies are predetermined. In this paper, we propose a Dynamic Multilevel Priority (DMP) packet scheduling scheme. In the proposed scheme, each node, except those at the last level of the virtual hierarchy in the zone-based topology of WSN, has three levels of priority queues. Real-time packets are placed into the highest-priority queue and can preempt data packets in other queues. Non-real-time packets are placed into two other queues based on a certain threshold of their estimated processing time. Leaf nodes have two queues for real-time and non-real-time data packets since they do not receive data from other nodes and thus, reduce end-to-end delay. We evaluate the performance of the proposed DMP packet scheduling scheme through simulations for real-time and non-real-time data. Simulation results illustrate that the DMP packet scheduling scheme outperforms conventional schemes in terms of average data waiting time and end-to-end delay.

A priority based packet scheduling scheme is proposed which aims at scheduling different types of data packets, such as real time and non-real-time data packets at sensor nodes with resource constraints in Wireless Sensor Networks. Most of the existing packet-scheduling mechanisms of Wireless Sensor Networks use First Come First Served (FCFS), non-preemptive priority and preemptive priority scheduling algorithms. These algorithms results in long end-to-end data transmission delay, high energy consumption, deprivation of high priority real-time data packets also it results in improper allocation of data packets to queues. Moreover, these algorithms are not dynamic to the changing requirements of Wireless Sensor Network applications since their scheduling policies are predetermined. In this paper, each node has three levels of priority queues. Real-time packets are placed into the highest-priority queue and can preempt data packets in other queues. Non-real-time packets are placed into two other queues based on a certain threshold of their estimated processing time. Leaf nodes have two queues for real-time and non-real-time data packets since they do not receive data from other nodes and thus, reduce end-to-end delay. The priority packet scheduling scheme outperforms conventional schemes in terms of average data waiting time and end-to-end delay and also it reduces sensor energy consumption.

Most of the existing packet scheduling mechanisms of the wireless sensor network use First Come First Served (FCFS) non pre emptive priority and pre emptive priority scheduling algorithms. The above algorithms have high processing overhead and also long end-to-end data transmission delay. In FCFS concept the data packet which is entering the node first will go out first from the node, and the packet which will enter last will leave at last. But in FCFS scheduling of real time data packets coming to the node have to wait for a long time period.In non pre emptive priority scheduling algorithm there is starvation of real time data packets because once the processor enters the running state, it will not allow remove until it is completed, so there is starvation of real time data packets. In pre emptive scheduling, starvation of non real time data packets, due to continuous arrival of real time data. Therefore the data packets are to be schedule in multilevel queue. But the multilevel queue scheduling scheme is not suitable for dynamic inputs, and hence the scheme is designed for dynamically change in the inputs. The Dynamic Multilevel Priority (DMP) packet scheduling is the scheme for dynamically changes in the inputs. In this scheme each node except the last level of the virtual hierarchy in the zone based topology of wireless sensor network has three levels of priority queues. Real time data packets are placed into highest priority queue and can preempt the data packets in the other queues. Non real time data packets are placed into other two queues based on threshold of their estimated processing time. The leaf node have two queues, one for real time data packet and another for non real time data packet since they do not receive data from other nodes and thus reduces end to end delay. This scheme reduces the average waiting time and end-to -end delay of data packets.

Scheduling different types of packets such as real-time and non-real time data packets in wireless links is necessary to reduce energy consumption of the wireless device. Most of the existing packet scheduling mechanism uses opportunistic transmission scheduling, in which communication is postponed upto an acceptable time deadline until the best expected channel conditions to transmit are found. This algorithm incurs a large processing overhead and more energy consumption. In this paper we propose a Packet Scheduling algorithm. In which, the ready queue is partitioned into three levels of priority queues. Real-time packets are placed into the highest priority queue and non-real time data packets are placed into two other queues. We evaluate the performance of the proposed Packet Scheduling scheme through simulations for real-time and non-real time data. Simulation results illustrate that the Dynamic Multilevel Priority packet scheduling scheme overcomes the conventional methods interms of average data waiting time and end-to-end delay, packet since they do not receive data from other nodes and thus reduces end to end delay. This scheme reduces the average waiting time and end-to-end delay of data packets.

Wireless Sensor Networks (WSNs) has become a popular research topic due to its resource constraints. Energy consumption and transmission delay is crucial requirement to be handled to enhance the popularity of WSNs. In order to overcome these issues, we have proposed an Efficient Packet Scheduling Technique for Data Merging in WSNs. Packet scheduling is done by using three levels of priority queue and to reduce the transmission delay. Real-time data packets are placed in high priority queue and Non real-time data packets based on local or remote data are placed on other queues. In this paper, we have used Time Division Multiple Access (TDMA) scheme to efficiently determine the priority of the packet at each level and transmit the data packets from lower level to higher level through intermediate nodes. To reduce the number of transmission, efficient data merge technique is used to merge the data packet in intermediate nodes which has same destination node. Data merge utilize the maximum packet size by appending the merged packets with received packets till the maximum packet size or maximum waiting time is reached. Real- time data packets are directly forwarded to the next node without applying data merge. The performance is evaluated under various metrics like packet delivery ratio, packet drop, energy consumption and delay based on changing the number of nodes and transmission rate. Our results show significant reduction in various performance metrics

In wireless sensor network (WSN) we need to schedule different types of packets, Such as real time and non real time packets with some restrictions on resources. There are lots of existing packet scheduling mechanism of wireless sensor network uses first come first serve (FCFS), preemptive priority and non-preemptive priority scheduling algorithm. Our focus to improve delivery ratio, average packet delay and throughput. The algorithm which is not dynamic gives long end to end delay and high processing overhead transmission in wireless sensor network. These algorithms are not dynamic in nature so there scheduling policies are pre determine. To solve these problems, we propose a dynamic multilevel priority packet scheduling method. In this scheme each node has three types of priority queues, real time data packets are put into the higher priority queue and they can preempt packets present in supplementary queues. Non real time packets are put into to other queues which are based on threshold of their probable dispensation time. Lower level nodes have two queues for non real time and real time packets so from other nodes they do not gather data and reduce end to end delay transmission. The dynamic multi priority data packet scheduling method do better than conventional scheme in terms of throughput and end to end delay transmission. This paper present a fuzzy based algorithm to overcome all related problems which are explained earlier other advantage of using fuzzy logic is that it does not require complex mathematical calculations. The simulation of the proposed algorithm is performed using NS2 and the results shows that the proposed algorithm satisfactorily fulfill the system requirements.

Packet scheduling is one of the critical issues in wireless sensor networks. In WSNs most existing scheduling mechanisms use FCFS, non-preemptive or preemptive priority algorithms. However, most of these algorithms incur high processing overhead and high end-to-end transmission delay due to the FCFS concept and starvation of real time and nonreal time data packets in non-preemptive and preemptive priority scheduling algorithms. Also, these packet scheduling algorithms are predetermined and hence cannot change in application requirements of WSNs. Therefore, in this paper, we propose a dynamic multilevel priority (DMP) packet scheduling algorithm to overcome the short comes like starvation of real time data, end-to-end or data transmission delay, and to make the packet scheduling dynamic. It is well known that in DMP scheduling scheme, nodes are organized in hierarchical structure and each node (except those nodes which are located at last level of hierarchical structure) has three level of priority queues in which real time data packets go to highest priority queue and non-real time data packets go to other two queues based on certain threshold levels of their estimated processing time. The DMP scheme proposed in this work was implemented with network simulator (NS2) v.2.32. The results obtained (end-to-end delay, average waiting time, network lifetime, and energy consumption) indicate the proposed DMP scheme is superior to existing first come first serve (FCFS) packet scheduling scheme. General Terms Wireless Sensor Network, FCFS.

Because wireless sensor networks (WSNs) have low-constrained batteries, optimizing the network lifetime is a primary challenge. Rechargeable batteries are a solution to prolong the lifetime of a sensor node instead of restricting their functionalities to save energy. Wireless energy transmitters have the added benefit of providing a charger for the batteries of the sensor nodes in the WSN. However, scheduling one or more charging vehicles efficiently to recharge multiple sensor nodes is challenging. In this context, this paper provides a solution to recharge the sensor nodes using charging vehicle scheduling in WSNs through a mixed linear programming approach. Initially, we identify a heuristic value of each sensor node based on their residual energy, distance from a charging vehicle, available data packets, and other metrics. Further, a set of nodes is recharged by identifying the best charging vehicle to prolong their lifetimes, as well as the lifetime of the network as a whole. We simulated the proposed approach using a Python simulator, tested using different performance metrics, and compared using the recently published works. We notice the superior performance of the proposed work under various metrics in time and query-driven WSNs.

ABSTRACTRecently, Packet scheduling plays a vital role in Wireless Sensor Networks (WSNs). The major key challenges include delay, packet dropping, energy consumption and lifetime due to constraints in energy and computing resources. All the research works on packet scheduling scheme in WSN uses only First Come First Served (FCFS) and Dynamic Multilevel Priority (DMP) schemes. FCFS works based on packet arrival time, it leads to starvation and high processing overhead for real-time packets. DMP works in multilevel with dynamic priority reduces the transmission overhead and bandwidth; it consumes more resources for real-time task leads to deadlock. To solve these problems, this work presents Multilevel Dynamic Feedback Scheduling (MDFS) algorithm. The sensor node classifies the emergency and normal data into three different ready queues named as high, medium and low priority, respectively. The queues are connected with a feedback mechanism; each packet from the sensor node has its own time quantum value based on the deadline. The updated time quantum value is compared with the boundary value of the queues, depends on the updated value the data packets are moved between queues with help of feedback mechanism. The simulation result proves that the projected MDFS outperforms in WSN environment.

Scheduling real-time and non-real time packets at the sensor nodes is significantly important to reduce processing overhead, energy consumptions, communications bandwidth, and end-to-end data transmission delay of Wireless Sensor Network (WSN). Most of the existing packet scheduling algorithms of WSN use assignments based on First-Come First-Served (FCFS), non-preemptive priority, and preemptive priority scheduling. However, these algorithms incur a large processing overhead and data transmission delay and are not dynamic to the data traffic changes. In this paper, we propose three-class priority packet scheduling scheme. Emergency real-time packets are placed into the highest priority queue and can preempt the processing of packets at other queues. Other packets are prioritized based on the location of sensor nodes and are placed into two other queues. Lowest priority packets can preempt the processing of their immediate higher priority packets after waiting for a certain number of timeslots. Simulation results show that the proposed three-class priority packet scheduling scheme outperforms FCFS and multi-level queue schedulers in terms of end-to-end data transmission delay.

There are many real time environment in which the use of wireless sensor networks (WSNs) is growing, especially the applications like military, health monitoring, security monitoring etc. WSN is nothing but collection of small, tiny sensor nodes which is having resource constraints like battery life. Therefore many research comes on WSNs are targeted on improving the energy efficiency of WSNs and extend the lifetime. In this paper, we are focusing to work on packet scheduling scheme which plays vital role to improve the energy efficiency and QoS performances. Currently there are many packet scheduling schemes used by researchers in WSNs applications such as First Come First Serve (FCFS), preemptive priority scheduling, non-preemptive priority scheduling methods. However this method suffered from limitations like higher routing overhead, more end to end delay and hence more energy consumption. In this paper, we are aiming to investigate new algorithm which overcomes the limitations of this existing method and achieves the better QoS and less energy consumption results. The investigated algorithm is called Dynamic Multilevel Priority (DMP) scheduling method. As the name indicates, this method works dynamically and as per the requirement of packet scheduling. There are three queues used by this algorithm for priority scheduling and applications like real time, non-real time. In first queue, real time packets processed with highest priority. In second queue, non-real time data packets processed with highest priority than third queue. In third queue, non real time data packets those are sensed at local are processed. The practical evaluation of this method is done using NS2.

The packet scheduling is essential and plays an important role to sense the element nodes with resource constraints in Wireless Networks. The packet scheduling scheme also scale the energy consumption and end-to-end information transmission delay in time period and non-real-time information packets during wireless transmission. The proposed Priority based Packet Scheduling (PPS) technique has a tendency to overcome the issues based on priority queues in a wireless network. The priority queue has three levels at each node, except those at the last virtual hierarchy level in the zone-based topology of wireless network. In the meantime packet square are measured and placed in the highest-priority queue and might pre-empt information packets in alternative queues. In the non-real-time period packet square are measured and placed into two alternative queues supported at a particular threshold of their calculable interval. The time period and non-real time information has two queues in a leaf node, since they did not receive information from alternative nodes which causes scale back end-to-end delay. The proposed PPS technique has affinity to evaluate performance through simulations for the time period and non-real-time information. Simulation results illustrate that the PPS Scheme outperforms typical schemes in terms of average information waiting time and end-to-end delay.

In order to increase the lifetime of entire wireless sensor network, the task scheduling in the network demands to achieve as far as possible the shortest task completion time, the lowest level of energy consumption and the highest level of balanced use of energy under condition of limitation in energy of nodes. Therefore, traditional multiprocessor Directed Acyclic Graph (DAG) scheduling algorithm can not be directly applied to sensor task scheduling. This paper proposes a Multi-objective Optimal DAG Scheduling (MODAGS) algorithm for wireless sensor networks. Its central idea is to exploit heuristic optimization algorithms and strategies respectively to realize multi-objective optimization in the task scheduling of wireless sensor networks. Then, take those results of single-objective optimal task scheduling as the initial particle swarm in the Particle Swarm Optimization (PSO) algorithm. By way of redefinition of operations in the PSO algorithm, the task scheduling in wireless sensor networks is optimized synthetically. Experimental results show that: combining heuristic optimization algorithm with bionic algorithm, the optimization technology has good realtime performance and high efficiency of energy.

In this paper we propose an optimal deployment and distributed packet scheduling of multi-sink Wireless Sensors networks (WNSs). This work is devoted to computing the optimal deployment of sinks for a given maximum number of hops between nodes and sinks. We also propose an optimal distributed packet scheduling in order to estimate the minimum energy consumption. We consider the energy consumed due to reporting, forwarding and overhearing. In contrast to reporting and forwarding, the energy used in overhearing is difficult to estimate because it is dependent on the packet scheduling. In this case, we determine the lower-bound of overhearing, based on an optimal distributed packet scheduling formulation. We also propose another estimation of the lower-bound in order to simulate non interfering parallel transmissions which is more tractable in large networks. We note that overhearing largely predominates in energy consumption. A large part of the optimizations and computations carried out in this paper are obtained using ILP formalization.

Wireless Sensor Networks (WSNs) consist of a large number of small and low cost sensor nodes powered by small batteries and equipped with various sensing devices. Usually, for many applications, once a WSN is deployed, probably in an inhospitable terrain, it is expected to gather the required data for quite some time, say for years. Since each sensor node has limited energy, these nodes are usually put to sleep to conserve energy, and this helps to prolong the network lifetime. There are two major approaches to sleep scheduling of sensor nodes, viz. (i) random (ii) synchronized. Any sleep scheduling scheme has to ensure that data can always be routed from source to sink. In this paper, we propose a novel approach for sleep scheduling of sensor nodes using a tree and an energy aware routing protocol which is integrated with the proposed sleep scheduling scheme. The tree is rooted at the sink node. The internal nodes of the tree remain awake and the leaf nodes are made to sleep. This provides an assured path from any node to the sink node. The tree is periodically reconstructed considering the remaining energy of each node with a view to balance energy consumption of nodes, and remove any failed nodes from the tree. The proposed approach also considerably reduces average energy consumption rate of each node as we are able to put more number of nodes to sleep in comparison to other approaches. Additional fault-tolerance is provided by keeping two paths from each node towards the sink. Extensive simulation studies of the proposed routing protocol has been carried out using Castalia simulator, and its performance has been compared with that of a routing protocol, called GSP, which incorporates sleep scheduling using random approach. The simulation results show that the proposed approach has longer network lifetime in comparison to that provided by GSP, and the energy consumption of nodes is also balanced.