With the widespread applications of Internet of Things (IoT), the emergency response performance for large-scale network packets is facing serious challenge, especially for renewable distributed energy resources monitoring in a smart grid. Therefore, how to improve the real-time performance of the emergency data packets has been a critical issue. Traditional packet scheduling schemes and topology optimization strategies are not suitable for a large-scale IoT-based smart grid. To address this problem, this paper proposes a new packet scheduling scheme named LOES, which first combines the priority-based packet scheduling scheme with local optimization. We exchange local geographic information to reduce the hop counts and distance between distributed source nodes and sink nodes. Each destination node determines the packet scheduling sequence according to the received emergency information. Finally, we compare LOES with first come first serve, multilevel scheme, and dynamic multilevel priority packet scheduling scheme using packet loss rate, packet waiting time, and average packet end-to-end delay as metrics. The simulation results show that LOES outperforms these previous scheduling schemes.

A Local-Optimization Emergency Scheduling Scheme With Self-Recovery for a Smart Grid

This paper surveys the energy-efficient routing protocols in wireless sensor networks (WSNs). It provides a classification and comparison following a new proposed taxonomy distinguishing nine categories of protocols, namely: Latency-aware and energy-efficient routing, next-hop selection, network architecture, initiator of communication, network topology, protocol operation, delivery mode, path establishment and application type. We analyze each class, discuss its representative routing protocols (mechanisms, advantages, disadvantages…) and compare them based on different parameters under the appropriate class. Simulation results of LEACH, Mod-LEACH, iLEACH, E-DEEC, multichain-PEGASIS and M-GEAR protocols, conducted under the NS3 simulator, show that the routing task must be based on various intelligent techniques to enhance the network lifespan and guarantee better coverage of the sensing area.

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Comparative Study of Energy Efficient Routing Techniques in Wireless Sensor Networks

With the applications of Internet of Things (IoT) for smart cities, the real-time performance for a large number of network packets is facing serious challenge. Thus, how to improve the emergency response has become a critical issue. However, traditional packet scheduling algorithms cannot meet the requirements of the large-scale IoT system for smart cities. To address this shortcoming, this paper proposes EARS, an efficient data-emergency-aware packet scheduling scheme for smart cities. EARS describes the packet emergency information with the packet priority and deadline. Each source node informs the destination node of the packet emergency information before sending the packets. The destination node determines the packet scheduling sequence and processing sequence according to emergency information. Moreover, this paper compares EARS with a first-come, first-served, multilevel queue algorithm and a dynamic multilevel priority packet scheduling algorithm. Simulation results show that EARS outperforms these previous scheduling algorithms in terms of packet loss rate, average packet waiting time, and average packet end-to-end delay.

A Data-Emergency-Aware Scheduling Scheme for Internet of Things in Smart Cities

Generally, various traffic requirements in wireless sensor network are mostly dependent on specific application types, that is, event-driven, continuous, and query-driven types. In these applications, real-time delivery is one of the important research challenges. However, due to harsh networking environment around a node, many researchers usually take different approach from conventional networks. In order to discuss and analyze the advantage or disadvantage of these approaches, some comprehensive survey literatures were published; however they are either out of date or compiled for communication protocols on single layer. Based on this deficiency, in this paper, we present the up-to-date research approaches and discuss the important features related to real-time communications in wireless sensor networks. As for grouping, we categorize the approaches into hard, soft, and firm real-time model. Furthermore, in all these categories, research has been focused on MAC and scheduling and routing according to research area or objective in second level. Finally, the article also suggests potential directions for future research in the field.

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A Survey on Real-Time Communications in Wireless Sensor Networks

As data source for Big Data, wireless sensor networks play great role in data collection and dissemination. Specially, real-time communication remains one of the crucial research challenges, because of the high complexity and severe networking requirements on restrained node in wireless sensor networks. Moreover, current schemes are assumed to take general traffic model for real-time delivery so they lack adaptability. To solve this problem, few routing protocols have been designed to accommodate new real-time model, (m,k)-firm, which is regarded as the most applicable scheme for event as well as query based applications in wireless sensor networks. However, since current schemes for (m,k)-firm stream are proposed to support unicast communications only, they cannot be applied to multicast communications where many group members are willing to receive data packets from the sink node. To overcome this problem, we propose a new multicast scheme for (m,k)-firm stream to deliver data packet to group members. To construct a multicast tree, different types of overlay tree are constructed according to distance based priority (DBP) value. Simulation results prove that the proposed scheme can meet (m,k)-firm requirement and have longer network lifetime than existing schemes.

An Efficient Real-Time Data Dissemination Multicast Protocol for Big Data in Wireless Sensor Networks

Wireless sensor networks can be termed as a new generation of distributed embedded systems that has a capability of meeting broad range of real-time applications. Examples include radiation monitoring, fire monitoring, border surveillance, and medical care to name but a few. Wireless sensor networks that are deployed in time/mission-critical applications with highly dynamic environments have to interact with the physical phenomenon under stringent timing constraints and severe resource limitations. For such real-time wireless sensor networks, designing and developing a real-time routing protocol that meets the required real-time guarantee of data packets communication is a stimulating field of study that raised many challenges and research issues. In this paper, we present a comprehensive survey of real-time routing protocols in WSN, by discussing each protocol with its key features. Finally, we concluded this paper with open research issues and challenges of real-time routing in WSN.

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Real -time routing protocols for wireless sensor networks : a survey

A packet-scheduling scheme that determines the order of servicing of incoming packets in an intermediate node plays a vital role in deciding the queuing delay experienced by a packet in a Wireless Sensor Network. In case of Real-time WSN applications, minimizing the End-to-End delay is a major concern to meet the required bounded time constraints. Therefore, a Real-time packet-scheduling scheme has to schedule the incoming packets effectively based upon their deadline by minimizing the queuing delay incurred at each node. In this paper, we presented the role of Real-time packet scheduling policy for Real-time Wireless Sensor Networks and we proposed an effective scheduling scheme that aids to Real-time data communication. Simulation result shows that the proposed scheduling policy works better in terms of average delay, packet drop ratio and packet miss ratio.

Pradeep Chennakesavula

Papers

Real -time routing protocols for wireless sensor networks : a survey

Real-time packet scheduling for real-time wireless sensor networks