Analysis of End-to-End Packet Delay for Internet of Things in Wireless Communications

Abstract

Accurate and efficient estimators for End to End delay (E2EPD) plays a significant and critical role in Quality of Service (QoS) provisioning in Internet of Things (IoT) wireless communications. The purpose of this paper, on one hand, is to propose a novel real-time evaluation metrics, on the other hand, addresses the effects of varying packet payload (PP) size. These two objectives rely on the analysis of E2EPD for QoS provisioning in multi-hop wireless IoT networks through multiple hops count from source to destination. The results of this study show the critical effect of PP size, hops count and interface speed on the improving E2EPD use of applications requiring real-time IoT communications.

IoT Provisioning QoS based on Cloud and Fog Computing

“…[95] Achieve green computing while providing QoS for end-users is a challenge A Delay-Base Workload Allocation (DBWA) algorithm based on Lyapunov drift-plus-penalty theory [96] Accurate and efficient End-toend delay (E2ED) estimators are significant for designing efficient QoS provisioning scheme for IoT systems.…”

“…End-to-End Delay (E2ED) estimators are significant for designing efficient QoS provisioning scheme for IoT systems. Therefore, Maslouhi et al [96] proposed real-time evaluation metrics and addressed varying packet payload (PP) size effects in multi-hop wireless IoT networks through counting hops from source to destination. The authors considered the following four elements (Radio propagation delay, Transmission delay, Queueing delay and Signal processing delay) that contribute to the end-to-end packet delay in one direction from source to destination in their theoretical study.…”

“…Latency [79, 81, 82, 84 -86, 88, 91 -97] Network Usage [79, 87, 91 -94, 97, 98] Service Time [79,83,97] RAM Consumption [79] CPU Utilization [79] Stability [80, 91, [94] Scalability [80,88] Energy efficiency [80,82,90,93,95] Throughput [81,82,85,87,[91][92][93][94]98] Availability [81,[86][87][88][90][91][92] Reliability [82, 84, 87-93, 96, 98] Response Time [83,97] jitter [84,96] Device/Network Cost [88-[90, 97] V. CONCLUSION All the mentioned studies had legit problems to solve, and they addressed it with brilliant solutions. According to Table II, the commonly considered QoS metrics are Latency, Reliability, Throughput, and Network Usage.…”

Weight Influence of Logarithmic and Exponential Functions on the Selection of Wireless Networks Using Multi-Criteria Decision-Making Methods

“…This parameter allows us to study packet queueing delays [22] that consists of four elements. First, the transmission delay (packet length/ throughput) is a function of packet length and network bandwidth (bps) [23]. Second, the delay of radio propagation is calculated by (distance/transmission speed) [24].…”

A Survey on Error–Correcting Codes for Digital Video Broadcasting

“…From our perspective, the concatenated One Step Majority Logic Decodable (OSMLD) codes are also the best competitors of LDPC codes, which preset mighty error-correcting schemes due to the simplicity of their decoder. Hardware complexity exploitation of the future generation DVB can significantly improve our lives in several fields, namely medicine, agriculture, etc...Due to the power, frequency, and wide coverage area of DVB, the equipment of the future generation can optionally integrate internet of things technologies [112,113] and improve its hardware to benefit from each broadcasting station's coverage areas. Either for cities (to make them smarter) or companions (to make them intelligent) because the new applications of future generation broadcasting stations are strongly required.…”