An Adaptive Hierarchical Hybrid Multicast Based on Information-Centric Networking

Many information-centric services have emerged, such as IPTV and video conferencing. These services put a lot of demands on scalable multicast communication. However, traditional IP multicast has low adoption because of its poor scalability. Therefore, some stateless multicast methods were proposed, which encapsulate the destination’s information into the packet header without requiring routers to maintain the multicast forwarding state. However, stateless multicast also faces some problems, such as ingress router overload, high forwarding overhead, packet redundancy, etc. In addition, most multicast methods cannot optimize the multicast tree because the multicast flow is simply forwarded along the shortest path tree from the source to receivers. This paper proposes an Adaptive Hierarchical Hybrid Multicast (AHHM) based on Information-Centric Networking. To balance the forwarding states and forwarding overhead, AHHM is designed as a two-layer structure, in which the upper layer establishes a stateful main tree and the lower layer establishes several stateless sub trees. The router on the main tree is defined as the multicast join node (MJN), and AHHM uses the Name Resolution System to maintain the mapping between each multicast group name and corresponding MJNs. To optimize the multicast transmission path, we designed the minimum cost selection strategy for users to select the appropriate MJN to join. Simulation results show that compared with Source-Specific Multicast (SSM) and Bit Index Explicit Replication (BIER), AHHM can not only reduce the multicast forwarding states but also reduce the control overhead and link load.

A Boltzmann Machine Optimizing Dynamic Routing for FANETs

Routing optimization for FANETs is a kind of NP-hard in the field of combinatorial optimization that describes simple and difficult to handle. The quality of routing has a direct impact on the network quality of FANETs, and the design of routing protocols becomes a very challenging topic in FANETs. In this paper, we study the characteristics of dynamic routing, combine the characteristics of FANETs themselves, use the energy of nodes, bandwidth, link stability, etc. as the metric of routing, and use Boltzmann machine for routing search to form an optimized dynamic routing protocol. The NS3 simulation simulator is used to compare and study with traditional MANET dynamic routing AODV and DSR, and the simulation results show that the routes obtained by using Boltzmann machine search are better than AODV and DSR in many aspects such as end-to-end average delay, average route survival time and control overhead.

Integrated data aggregation with fault-tolerance and lifetime energy-aware adaptive routing in coffee plantations using WSNs

The pest namely coffee white stem borer (CWSB) has harmed the economic progress of many emerging countries as a result of arabica coffee’s agricultural products. The boring activity causes the stem to shrink, fade in color, and acquire translucent margins across the stem. The pest multiplier can be controlled by capturing the location with the utilization of a wireless sensor networks (WSNs) and blocking its exit point at the user end. In this work, we propose an integrated data aggregation with faulttolerance and lifetime energy-aware adaptive routing (IDALAR) approach to transfer the sensed pest location data. The efficient packet format and statistical models based routing between clusterheads (CHs) and base station (BS) is proposed considering the availability of resources such as message overhead, algorithmic complexity, residual energy, and control overhead are all used to calculate its performance.

TACA: Trust Aware Clustering using ACO for Secure and Reliable Vehicular Ah hoc Network Routing

In the modern era, the Vehicular Ad-hoc Network (VANET) received significant attention for information sharing among the societies. The emerging Internet of Things (IoT) for smart city perspective boosts the development of VANET based applications such as road safety and Intelligent Transport System (ITS). The efficiency of such networks is a widely studied research problem. The clustering has shown an efficient technique to address the challenges of VANET QoS and computational efficiency. The vehicles are grouped according to certain conditions to form the cluster. In this way, the entire network divides into different clusters. Each cluster consists of limited vehicles with its leader called Cluster Head (CH). But the major challenge for VANET clustering has related to the stability of the cluster. Due to high network dynamics, the unreliability for CH selection and data relaying becomes a security threat in VANET. To address such a security threat of VANET clustering, we proposed Trust-Aware Clustering using Ant Colony Optimization (TACA) protocol. For each cluster, an ACO-based optimal CH selection algorithm applying different trust components of the vehicle. The ACO solves the problem of optimal CH selection with minimum control overhead and maximum CH lifetime. The optimal CH selected has been selected based on trust-aware ACO fitness function using the parameters such as vehicle speed, Degree of Connectivity (DoC), vehicle congestion, and Packet Relaying Probability (PRP). This mechanism enables clusters to select reliable CH to address the security concerns of VANET communications. The TACA protocol has been evaluated with recent similar methods, and the results demonstrate efficiency in terms of QoS and computational overhead of clustering.

Congestion-aware and Predictive Geo-Casting Routing Mechanisms for Mobile ad hoc Network

Mobile Ad-hoc Networks (MANETs) has gained remarkable appreciation during the last decade because of its high flexibility. Due to high mobility and unpredictable topology changes, most of the existing routing protocols are unable to adapt to these changes and efficient route selection becomes a challenging task. The existing routing protocols incur high control overhead during route discovery process, tendency to select an unreliable route and high data packet loss during route maintenance. Therefore, this paper presents A Congestion-aware and Predictive Geo-casting Routing Mechanism (CPGR) for MANET that optimally utilize the constrained network resources and reliably detect high-quality links. CPGR exploits a multi-facet routing strategy that takes into consideration the congestion level, relatively higher signal strength, and hop-counts of neigh- boring nodes while making routing decisions. This strategy not only ensures data dissemination via high quality nodes but also balances out resource consumption among nodes while traversing through shorter paths. Demonstrated by simulation results in NS-2, CPGR achieves improved performance in terms of end-to-end delay, control overhead, and packet delivery ratio as compared to existing solutions.

Throughput of distributed queueing-based LoRa for long-distance communication

LoRa, due to its advantage of long-range communication capability, is promising for Internet of Things (IoT) and space-air-ground communications. However, the conventional MAC protocol used with LoRa is classified as an Aloha-based algorithm, which leads to drastic decrease in throughput when a huge amount of end-devices try to access the network. To achieve stable and high throughput of LoRa, we propose a design to combine the distributed queueing (DQ) and in-band-full-duplex (IBFD) technologies. The usage of DQ mechanism is benefit for fast collision resolution, while the IBFD-enabled gateway helps to reduce the heavy control overhead of DQ. The designs of access procedure and frame structure are discussed in detail. The outage probability and average throughput are evaluated under imperfect self-interference cancelation. Also, a mathematical programming method is developed to optimize the spreading factor and code rate. Numerical results show that our proposal gains an extra enhancement of 1.83-fold in throughput.

ACOLBR: ACO Based Load Balancing Routing In MANET

Real-time data transmission is one of the objectives of MANET (mobile ad-hoc network) to handle emergencies like a forest fire, flood, and earthquake. In this scenario, quick delivery of data is itself a challenging task for MANET and there is a possibility of load imbalance due to packet transmission in between source-destination pairs via the shortest path due to congestion or control overhead. In this paper, a novel routing protocol, called ACOLBR (ACO based load balancing routing), is design to control the congestion and balancing the load among the multiple paths in between source to destination. The similarity between the environment of Ant Colony and the MANET inspires the authors to apply ACO (Ant colony optimization) technique during routing in MANET to control congestion and balance the load in the network. In our proposal, two colonies of ants (red/blue) carry their packets based on the network condition. A decision variable is designed to select red/blue ant for transferring packets based on different network parameters such as bandwidth, energy, mobility, and distance. The selection of red ant means the route where the concentration of red pheromone is maximum and reverse is true for blue ant. This protocol is also concerns about the link failure during packet transmission in a route. Simulation results using OMNET++ show that ACOLBR outperforms ARA, ANTHOCNET, FACO, AODV, DSDV, DSR, CA-ARTT, and MOAODV in terms of load balancing efficiently in the route for data transmission in between source to destination.

A novel method of mobility-based clustering protocol in software defined sensor network

The distributed clustering method is widely used to extend network lifetime in traditional wireless sensor networks. However, it is difficult to achieve the idea performance of the whole network, such as transmission rate, energy consumption, and control overhead, neglecting the global stability of the network. To tackle this problem, a centralized mobility-based clustering (CMBC) protocol is proposed in the software defined sensor network. The method of CMBC mainly consists of two aspects: first, CMBC clusters the nodes with the connection time between the mobile nodes (i.e., noncluster head nodes, non-CH) and the cluster head (CH) and establishes stable topological structures between the non-CHs and the CH; second, when emergencies occur, the centralization management control center sends the configuration files to replace the CH. Compared to the distributed network of MBC, WCRA and IMP-MECA protocol, the proposed method can be applied in scenarios with high-speed mobile nodes to improve the network performance in terms of transmission successful rate, average power consumption, and average control overhead.

Throughput of Distributed Queueing Based LoRa for Long-Distance Communication

LoRa, due to its advantage of long-range communication capability, is promising for Internet of Things (IoT) and space-air-ground communications. However, the conventional MAC protocol used with LoRa is classified as an Aloha-based algorithm, which leads to drastic decrease in throughput when a huge amount of end-devices try to access the network. To achieve stable and high throughput of LoRa, we propose a design to combine the distributed queueing (DQ) and in-band-full-duplex (IBFD) technologies. The usage of DQ mechanism is benefit for fast collision resolution, while the IBFD-enabled gateway helps to reduce the heavy-control-overhead of DQ. The designs of access procedure and frame structure are discussed in detail. The outage probability and average throughput are evaluated under imperfect self-interference cancellation. Also, a mathematical programming method is developed to optimize the spreading-factor and code-rate. Numerical results show that our proposal gains an extra enhancement of 1.83-fold in throughput.