By Samia Allaoua Chelloug
Networks and Communication Systems Department,
College of Computer and Information Sciences,
Princess Nourah Bint Abdul Rahman University, Riyadh, KSA
Routing is a topic that has attracting the research community in last years and intense works have been devoted to this field. Traditional routing protocols for Ad hoc networks may fall into three categories: reactive, proactive, and hybrid protocols.
The first category establishes a route on demand; while, the second one maintains the topology and updates the routing tables periodically. The hybrid protocols perform both reactive and proactive routing to reduce the delay. Later, new protocols for sensor networks have been proposed. Two features are handled in such protocols: data exchange is performed hop by hop and the lifetime of the network is maximized.
Routing in IoT systems is highly related to routing in Ad hoc and sensor networks. Energy consumption of sensors, mobility of things, and the type of the IoT’s middleware are three primary concerns that may affect routing in IoT. 6LoWPAN (IP6 over power personal area networks) is a major routing protocol for IoT systems. It has been defined by the Engineering Task Force (IETF) to route data through the Internet among non-IP sensors. It relies on IEEE 802.15.4 that is suitable for low power sensors. The network topology of 6LoWPAN includes a set of reduced function sensors that are connected to full function sensors. Moreover, a gateway is placed between two different network domains.
Image Attribute: Texas Instruments
By another hand, the network stack of 6LoWPAN is composed of seven layers: the IEEE 802.15.4 physical and Mac layers, the adaptation layer, IPV6, the transport, and the application layers. More specifically, the physical layer of IEEE 802.15.4 provides 27 channels that operate in different frequency bands with varying data rates (20 - 250 Kbps). The Mac layer manages the medium via the CSMA/CA protocol and ensures also the device’s association, disassociation, and synchronization. The function of the adaptation layer is to adapt IPV6 packets and fit them into the IEEE 802.15.4 format. It also ensures the fragmentation of IPV6 packets into Mac frames. The transport layer of the network stack adopts a simple transmission protocol which is the User Datagram Protocol (UDP).
The routing process in 6LoWPAN starts when a reduced function sensor has to send a packet to another IP sensor. In this case, the higher full function sensor that is connected to the reduced function sensor will be responsible to send the packet, hop by hop until it reaches the gateway. Actually, the gateway uses the IP address to locate the domain of the remote IP sensor.
Further, 6LoWPAN ad hoc on Demand Distance Vector Routing (Load) has been adopted for 6LoWPAN routing. Like AODV, Load uses route request and route reply messages but it does not use the sequence number. It also relies on the Link Layer Notification messages that approve the reception of Mac messages. It creates a mesh topology and runs on full function devices. A route is selected by Load if it includes a certain number of links such that their accumulated route cost (LQI)  is worse than a certain threshold. The route should also include less hops between the source and the destination. Hierarchical routing (HiLow) is another protocol that is used in 6LoWPAN to minimize the delay. The idea is to build a hierarchy and then 6LoWPAN device will either join an existing parent or become a parent.
According to 6LoWPAN is used for networks with high processing capabilities. For this end, Protocol for Low Power and Lossy Networks (RPL) has been designed for constraint devices in power, computation, and memory capabilities. RPL is a distance vector routing protocol that is based on IPV6. It builds a Destination Oriented Directed Acyclic Graph (DODAG). Many metrics may be used to construct a DODAG: the Expected Number of Transmissions (ETX), the remaining energy of the devices… Energy-Efficient Probabilistic Routing (EEPR) is an alternative solution for routing in an IoT environment. It is based on the same idea of AODV but the transmission of a RREQ packet follows a certain forwarding probability that depends on the residual energy and the ETX metric, The proposed mathematical equation shows that the forwarding probability will be high if the ETX metric is low and the residual energy is high.
The simulation results show that the variance of the residual energy of EEPR is smaller than the variance of the residual energy of AODV. The work in proposed the Context Awareness in Sea Computing Routing Protocol (CASCR). It exploits the idea of sea computing that was first announced at the Chinese Academy of Science High Technology Planning Seminar in 2010. The sea computing refers to the embodiment of autonomous devices into various things. It produces effective intelligent decisions through local interactions of the devices. CASCR associates a state and some operations to each device.
The states include: full-working, serving, single working, sleeping, and hibernating.
The set of operations contains: gather information, transmit information, apply information fusion, and generate a control operation.
In particular, CASCR predicts the new state of each device using Markov chains that defines the new state as a function of the device’s history. The device holding a routing request should send it to its first hop neighbors that are provided with a context data table which specifies the network topology in term of: neighbors, subordinators, superior, colleagues and disabled devices. The context data table is used to find the next hop.
The simulation results show that CASCR has low energy consumption. The research team associated with this article is involved in developing a cross-layer protocol to meet the performance parameters of IoT applications: minimum date delivery rate, and maximum packet delay. The proposed protocol runs on the top of IEEE 802.15.4. It combines the network topology information, the performance requirements and the link performance to decide on the next hop for routing data. It extends the ETX metric by considering the packet loss which may be generated by the MAC contention. The authors of conducted a simulation and demonstrated that the reliability metric is better than the ETX metric. The traditional routing protocols for Adhoc networks such as AODV, DSR, and OLSR, discussed and their performance were gauged in an IoT environment. Three metrics were used:
- Overhead: which is the result of the number of route packets by the number of data packets.
- Average end to end delay: concerns the total delay that is generated by route discovery, queuing.
- Throughput: it is the result of the number of packets received by the destination by the number of packets sent by the source.
The author proposed an Energy-Efficient Content-Based Routing (EECBR) protocol for the IoT that minimizes the energy consumption in a technical paper which contains simulation results that are based on the random waypoint mobility model. It illustrates that the overhead of the three protocols depends on the number of nodes. The percentage of mobile nodes is another parameter of the simulation. However, the authors did not define their network topology nor the IoT architecture.
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