Novel energy model to analyze the effect of MAC and network parameters on asynchronous IEEE 802.15.4 multi-hop wireless networks lifetime

Abstract

Abstract-Design of energy efficient wireless networks is the primary research goal for evolving billion device applications like Internet of Things (IoT), smart grids and Cyber Physical Systems (CPS). Energy efficient models can reduce megawatts of power through out globe thereby reducing carbon foot print by improving overall network lifetime of large scale networks. Recent advances in physical layer have optimized energy consumption of IEEE 802.15.4 Physical layer, but energy efficiency of MAC and network layers is also essential to realise Green wireless networks. Though anycast multi-hop communication is initiated by many recent researchers by obtaining reliability, delay and energy expressions, still there is no model that captures relay nodes state wise behaviour effectively. In this paper a new energy model with 3-dimensional Markov MAC model with generalized anycast routing and state behaviour is proposed and developed for asynchronous wireless ad hoc networks. Proposed state behaviour of node model has consideration of MAC and network parameters like minimum backoff exponent, maximum backoff stages and retries along with network parameters like packet length, wake up rate, Sleep, Idle-Listen, Active-Tx and Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) states. Results show that total energy of derived model depends on many network and MAC parameters. Affect of most of the considered parameters are analysed with simulation results. Total energy of the multi-hop network reduced to 25% with variation in minimum backoff exponent and increased by 45% with increase in packet length. It is observed that derived analytical energy model better fits with most of the parameters that affects energy.

A Smart Game for Data Transmission and Energy Consumption in the Internet of Things

“….56 * 10 −6 + 144.00 * 10 −6 w n−1 (1 + w) −n (28) For a packet of data, the energy used in transmitting the payload and receiving the ACK, E pack and the energy used for a CSMA E csma are relatively constant according to [48] and [49]. The variable in (22), (23) and 28is: p −1 = w n−1 (1 + w) −n . Therefore, we visualise the utility expression in (28) for 6 and 12 nodes by plotting the graph of utility against CW as shown in Fig.…”

Energy Efficient Medium Access Control Protocols for Wireless Sensor Networks – A Survey

“…Authors found their model efficient in achieving energy-efficiency; however other QoS aspects could not be addressed. Furthermore, considering applications such as IoT, Cyber Physical Systems (CPS) and smart grids Prasad et al [36] focused on state wise dynamic behaviour feature (of relay nodes) with 3-dimensional Markov MAC algorithm that achieved energy-efficient routing decision. Liu et al [37] aimed at enhancing the performance of EH-powered WSNs in three aspects: scheduling, relaying and MAC control.…”

Single CCA for IEEE 802.15.4 networks: a cross layer energy model

“…Some other related literature includes [9] where cross‐layer energy optimisation has been treated. Further, the authors presented an energy model of IEEE 802.15.4 in [10], considering sensing energy, CCA energy, and active mode energy to analyse the effect of MAC and other network parameters, but the authors have not considered energy consumption for the total frame transmission.…”