A Smart Collaborative Routing Protocol for Reliable Data Diffusion in IoT Scenarios

Abstract

It is knotty for current routing protocols to meet the needs of reliable data diffusion during the Internet of Things (IoT) deployments. Due to the random placement, limited resources and unattended features of existing sensor nodes, the wireless transmissions are easily exposed to unauthorized users, which becomes a vulnerable area for various malicious attacks, such as wormhole and Sybil attacks. However, the scheme based on geographic location is a suitable candidate to defend against them. This paper is inspired to propose a smart collaborative routing protocol, Geographic energy aware routing and Inspecting Node (GIN), for guaranteeing the reliability of data exchanging. The proposed protocol integrates the directed diffusion routing, Greedy Perimeter Stateless Routing (GPSR), and the inspecting node mechanism. We first discuss current wireless routing protocols from three diverse perspectives (improving transmission rate, shortening transmission range and reducing transmission consumption). Then, the details of GIN, including the model establishment and implementation processes, are presented by means of the theoretical analysis. Through leveraging the game theory, the inspecting node is elected to monitor the network behaviors. Thirdly, we evaluate the network performances, in terms of transmission delay, packet loss ratio, and throughput, between GIN and three traditional schemes (i.e., Flooding, GPSR, and GEAR). The simulation results illustrate that the proposed protocol is able to outperform the others.

Novel Reliable and Energy-Efficient Routing Protocols for Wireless Sensor Networks

“…Researchers of [21], improve the reliability by finding the best location of CH. RE-AEDG [22] and GIN [23] protocols use the cooperative routing model to enhance reliability, where the transmitted packet is overheard by several neighbors and retransmitted by several neighbors too. Some researches use network coding to improve reliability [24,25].…”

Towards Adaptive Multipath Managing: A Lightweight Path Management Mechanism to Aid Multihomed Mobile Computing Devices

“…The UPL and TML models were used to represent the distributed loss caused by wireless noise interference and the infrequent continuous loss caused by wireless signal fading, respectively [32]. In addition, in order to simulate the complex behaviors of Internet traffic [33], we attached each of the three paths to a VBR (Variable Bit-Rate) traffic generator to send the VBR cross-traffic to its corresponding sink. The packet size of the VBR cross-traffic utilized in the simulation was chosen as follows [34]: 49% were 44 bytes in length, 1.2% 576 bytes, 2.1% 628 bytes, 1.7% 1300 bytes, and the other 46% 1500 bytes in length, in which 90% of the VBR cross-traffic was transmitted by TCP technology and the remaining 10% by UDP technology.…”

Evolutionary Game Analysis of Three-Player for Low-Carbon Production Capacity Sharing

“…With the development of information technology such as Cloud Computing (CC), Internet of Things (IoT) [1], Artificial Intelligence (AI), Industrial Internet (II), and so on, a new term 'sharing economy' has rapidly spread around the world [2]. Its typical characteristics include the sharing of access rights, as well as the integration of massive and decentralized resources.…”

“…In summary, according to an overview of the production capacity sharing problem, although researchers have made significant progress in this field, the following questions and challenges are still open: (1) what are the low-carbon production capacity? (2) How to formulate and solve the three-player evolutionary game model for LCPC sharing problem?…”