PSA: The Packet Scheduling Algorithm for Wireless Sensor Networks

The main cause of wasted energy consumption in wireless sensor networks is packet collision. The packet scheduling algorithm is therefore introduced to solve this problem. Some packet scheduling algorithms can also influence and delay the data transmitting in the real-time wireless sensor networks. This paper presents the packet scheduling algorithm (PSA) in order to reduce the packet congestion in MAC layer leading to reduce the overall of packet collision in the system The PSA is compared with the simple CSMA/CA and other approaches using network topology benchmarks in mathematical method. The performances of our PSA are better than the standard (CSMA/CA). The PSA produces better throughput than other algorithms. On other hand, the average delay of PSA is higher than previous works. However, the PSA utilizes the channel better than all algorithms

A Five-Phase Reservation Protocol (FPRP) for Mobile Ad Hoc Networks

A new single channel, TDMA-based broadcast scheduling protocol, termed the Five-Phase Reservation Protocol (FPRP), is presented for mobile ad hoc networks. The protocol jointly and simultaneously performs the tasks of channel access and node broadcast scheduling. The protocol allows nodes to make reservations within TDMA broadcast schedules. It employs a contention-based mechanism with which nodes compete with each other to acquire the TDMA slots. The FPRP is free of the ``hidden terminal" problem, and is designed such that reservations can be made quickly and efficiently with minimal probability of conflict. It is fully distributed and parallel (a reservation is made through a localized conversation between nodes in a 2-hop neighborhood), and is thus arbitrarily scalable. A ``multihop ALOHA" policy is developed to support the FPRP. This policy uses a multihop, pseudo-Baysian algorithm to calculate contention probabilities and enable faster convergence of the reservation procedure. The performance of the protocol is studied via simulation, and the node coloring process is seen to be as effective as an existing centralized approach. Some future work and applications are also discussed

A Case for Time Slotted Channel Hopping for ICN in the IoT

Recent proposals to simplify the operation of the IoT include the use of Information Centric Networking (ICN) paradigms. While this is promising, several challenges remain. In this paper, our core contributions (a) leverage ICN communication patterns to dynamically optimize the use of TSCH (Time Slotted Channel Hopping), a wireless link layer technology increasingly popular in the IoT, and (b) make IoT-style routing adaptive to names, resources, and traffic patterns throughout the network--both without cross-layering. Through a series of experiments on the FIT IoT-LAB interconnecting typical IoT hardware, we find that our approach is fully robust against wireless interference, and almost halves the energy consumed for transmission when compared to CSMA. Most importantly, our adaptive scheduling prevents the time-slotted MAC layer from sacrificing throughput and delay

Optimal Fair Scheduling in S-TDMA Sensor Networks for Monitoring River Plumes

Underwater wireless sensor networks (UWSNs) are a promising technology to provide oceanographers with environmental data in real time. Suitable network topologies to monitor estuaries are formed by strings coming together to a sink node.This network may be understood as an oriented graph. A number of MAC techniques can be used in UWSNs, but Spatial-TDMA is preferred for fixed networks. In this paper, a scheduling procedure to obtain the optimal fair frame is presented, under ideal conditions of synchronization and transmission errors. The main objective is to find the theoretical maximum throughput by overlapping the transmissions of the nodes while keeping a balanced received data rate from each sensor, regardless of its location in the network. The procedure searches for all cliques of the compatibility matrix of the network graph and solves a Multiple-Vector Bin Packing (MVBP) problem. This work addresses the optimization problem and provides analytical and numerical results for both the minimum frame length and the maximum achievable throughput