E2E Delay Research Articles

A novel routing protocol for reducing packet delay with multi-beam antennas

Ad hoc networks are infrastructureless networks consisting of static and/or mobile nodes. These networks are deployed for a wide range of applications. Having an efficient routing protocol for communication between the nodes can be critical. Our goal in this paper is to design a routing protocol that capitalizes on Multi-Beam directional Antennas (MBAs) to significantly reduce the end-to-end (E2E) delay in multi-hop ad hoc networks that service multiple traffic flows. Previously, we proposed a multi-beam directional antenna MAC protocol, and a Mixed Integer Linear Programming model that exploits MBAs’ capabilities for delay minimization. Solving this model showed that the routes that are selected for different flows need to have certain key characteristics that depart from the traditional shortest-route philosophy. Based on these characteristics, we design, in this paper, an MBA-Delay-Reducing Routing protocol (MBA-DRR) that fully harnesses the benefits of MBAs for delay reduction. The benefits of this protocol apply to all types of multi-hop MBA-based ad hoc networks, both mobile and static. The evaluation on a multi-flow static scenario shows that MBA-DRR, with a delay of just 4.4 ms, gets very close to the optimal solution with a delay of 2.5 ms. Comparatively, Reactive-Geographic hybrid Routing, a shortest-route protocol, has a delay of 48 ms. An evaluation on a representative multi-flow mobile scenario shows that, while a single-beam directional MAC reduces the E2E delay from 700 ms to 40 ms, and a multi-beam directional MAC halves this to 20 ms, our proposed routing protocol further cuts it to 9 ms.

Forest Fire Detection Using New Routing Protocol.

The Mobile Ad-Hoc Network (MANET) has received significant interest from researchers for several applications. In spite of developing and proposing numerous routing protocols for MANET, there are still routing protocols that are too inefficient in terms of sending data and energy consumption, which limits the lifetime of the network for forest fire monitoring. Therefore, this paper presents the development of a Location Aided Routing (LAR) protocol in forest fire detection. The new routing protocol is named the LAR-Based Reliable Routing Protocol (LARRR), which is used to detect a forest fire based on three criteria: the route length between nodes, the temperature sensing, and the number of packets within node buffers (i.e., route busyness). The performance of the LARRR protocol is evaluated by using widely known evaluation measurements, which are the Packet Delivery Ratio (PDR), Energy Consumption (EC), End-to-End Delay (E2E Delay), and Routing Overhead (RO). The simulation results show that the proposed LARRR protocol achieves 70% PDR, 403 joules of EC, 2.733 s of E2E delay, and 43.04 RO. In addition, the performance of the proposed LARRR protocol outperforms its competitors and is able to detect forest fires efficiently.

Collision-free distributed MAC protocol for passive optical intra-rack data center networks

In this paper, we present a distributed medium access control (MAC) protocol and a network architecture suitable for optical intra-rack data center networks (DCNs). The intra-rack communication is performed using passive optical components, over four data wavelength division multiplexing (WDM) channels of either 40 or 100 Gbps each, keeping low power consumption. On the other hand, the inter-rack communication is performed over a separate network through upper layer routers. In this study, we focus only on the intra-rack communication. We introduce an intra-rack DCN (IR-DCN) architecture that works in the optical domain, and two IR-DCN configurations with different total nominal capacity: 160 and 400 Gbps, respectively. Also, we propose a synchronous pre-transmission coordination fair access intra-rack MAC (intra-MAC) protocol taking into account the traffic characteristics and priority classes within existing DCNs. The proposed intra-MAC protocol totally eliminates packet collisions, achieving high performance. Particularly, it reaches high bandwidth utilization even under heavy loads: 90% and 87.5% for the two IR-DCN configurations of 160 and 400 Gbps total capacity, respectively. Also, it achieves low mean end-to-end (e2e) packet delay, lower than 0.25 and 0.12 ms, respectively, providing a reliable solution for time-sensitive DCN traffic. Specifically, simulation results demonstrate that the highest priority traffic experiences e2e delay lower than 1.9 and 1.1 µs, respectively, which is sufficient for the service of the strictest delay requirements of time-sensitive cloud applications. The intra-MAC protocol is decentralized, without the need for a network controller, providing high flexibility. Our IR-DCN proposal is studied in comparison to other currently dominant intra-rack/cluster DCNs, and it achieves from 6% to 57% higher throughput and from 20% to 99% lower e2e delay at high loads. Comparatively, it is on average 80% and 68% more energy and cost efficient, respectively.

Cross-Layer and Energy-Aware AODV Routing Protocol for Flying Ad-Hoc Networks

In recent years, unmanned aerial vehicles (UAVs) have become the trend for different types of research and applications. UAVs can accomplish some technical and risky tasks while still being safe, mobile, and inexpensive to operate. However, UAVs need flying ad-hoc networks (FANET) to operate in inaccessible or infrastructure-less areas. Subsequently, in many military and civil applications, the UAVs are connected ad hoc. FANET-based UAV systems have been developed for search and rescue, wildlife surveys, real-time monitoring, and delivery services. Maintaining the reliability and connectivity among UAV nodes in FANET becomes challenging because of the UAV movement, environmental conditions, energy efficiency, etc. Energy-aware routing protocols have become essential for developing advanced and effective FANETs. This paper presents a proposed Cross-Layer and Energy-Aware Ad-hoc On-demand Distance Vector (CLEA-AODV) routing protocol for improving FANET performance. The CLEA-AODV protocol is mainly divided into three sections: routing with AODV protocol, Glow Swarm Optimization (GSO)-based Cluster Head Selection, and Cooperative Medium Access Control (MAC). The cross-layer approach is implemented on the network layer and the data layer. The major parameters considered to evaluate the performance of the FANET are Packet Success Rate (PSR), Throughput (TP), End-to-End (E2E) delay, and packet drop ratio (PDR). The Network Simulator version 2 (NS2) is used to implement the CLEA-AODV protocol and evaluate the network performance. The results are compared with the standard AODV, Self-Organization Clustering-GSO (SOC-GSO), and Energy Efficient Neuro-Fuzzy Cluster-based Topology Construction with Meta-Heuristic Route Planning (EENFC-MRP) protocols. The results show that the CLEA-AODV surpasses these protocols in terms of PSR, TP, E2E delay, and PDR.

Performance Analysis and Systematic Review of Privacy Preservation-Based Authentication Models and Cryptographic-Based Data Protocols

This paper proposes a privacy preservation-based data security and secure data protocol for distributed Data Storage and Communication (DSaC). An effective performance analysis is done between privacy preservation-based data security approach for authenticated encrypted access and secure data protocol for DSaC in cloud and the approaches are compared with the traditional schemes like Ins-PAbAC, Homomorphic Proxy Re-encryption (HPRE), LAM-CIoT, SA-EDS, Advanced Encryption Standard (AES), and Data Encryption Standard (DES). The proposed privacy preservation approach achieved a minimum time of 12614ms, maximum detection rate of 0.985, maximum privacy factor of 0.645, maximum TPR of 0.785, and maximum TNR of 0.777 for Switzerland dataset and the ACS-based secure data protocol achieved a minimum time of 5527ms, maximum detection rate of 0.953, minimum E2E delay of 85, maximum TPR of 0.817, and maximum TNR of 0.754 for Cleveland dataset.

Multi-Hop Relaying Distribution Strategies for Terahertz-Band Communication Networks: A Cross-Layer Analysis

Terahertz (THz) band (0.1-10 THz) communication is envisioned as a key wireless technology to satisfy the need for wireless Terabit-per-second (Tbps) links in 6G systems. The THz band supports very large channel bandwidths with the cost of very high propagation losses. On the one hand, the absorption by water vapor molecules manifests itself in the form of absorption lines that broaden in frequency with distance, resulting into a highly distance-dependent channel bandwidth. On the other hand, the very high spreading or free-space losses require the use of highly directional antennas (DAs) simultaneously in transmission and reception at all times. As with the bandwidth, the beamwidth of such DAs is also related with the transmission distance, and introduces severe synchronization and, correspondingly, delay challenges. These issues become even worse when the system needs to support up to Tbps peak data-rates. The end-to-end (E2E) delay and, correspondingly, effective throughput in multi-hop THz communication networks can drastically suffer if all these peculiarities are not taken into account. In this paper, multi-hop relaying distribution strategies are developed for THz-band communication to minimize the multi-hop E2E delay by considering cross-layer effects between the THz channel, highly DAs, nodes’ buffer and the physical, link and network layers.

Analysis and Countermeasures of Wormhole and Sinkhole Attacks in WBAN

Wireless Body Area Network (WBAN) is a promising technology that is having a significant number of applications in healthcare. Despite having several benefits, WBAN is susceptible to several security attacks, particularly related to the node misbehavior attacks such as sinkhole, wormhole, blackhole, and grayhole attacks. In this research work, the performance of the AODV protocol against wormhole and sinkhole attacks has been analyzed. This comparison-based study has been achieved for the PDR (Packet Delivery Ratio), NRL (Normalized Routing Load), residual energy, packet loss, average throughput, and average end-to-end delay metrics for WBAN with 20 and 50 nodes respectively. The results show that in 20 nodes network the PDR and average throughput of the sinkhole is 32% and 53% more than the wormhole attack, respectively. However, NRL is 36% and the average e2e delay is 63% less than the wormhole attack. In 50 nodes network, the PDR of a sinkhole attack is 26% and the average throughput is 10.7% more than the wormhole attack. Though, NRL and average e2e delays are 41.7% and 78.5% less than the wormhole attack, respectively. Hence, the wormhole attack in either network is more destructive than the sinkhole attack. Based on the simulation results, some solutions against the mentioned attacks have been recommended.

Can Terahertz Provide High-Rate Reliable Low-Latency Communications for Wireless VR?

Wireless virtual reality (VR), a key 3GPP use case of emerging cellular systems, imposes new visual and haptic requirements directly linked to the Quality of Experience (QoE) of VR users. These QoE requirements can only be met by wireless connectivity that offers high-rate and high-reliability low-latency communications (HR2LLC), unlike the low rates commonly associated with ultrareliable low-latency communication. The high rates for VR over short distances can only be supported by an enormous bandwidth, available in the terahertz (THz)-frequency bands. To explore the potential of THz for meeting HR2LLC requirements, a quantification of the risk for an unreliable VR performance is conducted through a novel and rigorous characterization of the tail of the end-to-end (E2E) delay. Then, a thorough analysis of the Tail-Value-at-Risk (TVaR) is performed to concretely characterize the behavior of extreme wireless events crucial to the real-time VR experience. In particular, the probability distribution function of the THz transmission delay is derived and then used to infer the system reliability scenarios with guaranteed Line of Sight (LoS) as a function of THz network parameters. Numerical results show that abundant bandwidth and low molecular absorption are necessary to improve the reliability. However, their effect remains secondary compared to the availability of LoS, which significantly affects the THz HR2LLC performance. In particular, for scenarios with guaranteed LoS, a reliability of 99.999% (with an E2E delay threshold of 20 ms) for a bandwidth of 15 GHz along with data rates of 18.3 Gbps can be achieved by the THz network, compared to a reliability of 96% for twice the bandwidth, when blockages are considered.

Hop-by-hop bandwidth allocation and deployment for SFC with end-to-end delay QoS guarantees

Network function virtualization and 5G network slicing technology can provide a more resilient and manageable Internet by deploying various requests on different slices. In this paper, we propose a hop-by-hop bandwidth allocation framework for service function chains (SFCs) to guarantee delay QoS constraints of requests. A end-to-end (E2E) SFC contains multiple virtual network functions (VNFs), which is constructed as a tandem queueing system. The arrival is modeled as an interrupted bernoulli process (IBP) or two-aggregation Markov modulated bernoulli process (2A-MMBP) to represent the traffic of typical services, data or video call. And the effective bandwidth (EB) formulas for these intricate Markovian processes are derived. Then we use EB/ effective capacity (EC) theory to allocate the bandwidth for SFCs hop by hop and deduce the service probabilities of the nodes. On the basis of EB/EC bandwidth allocation, the departure process is fitted into an IBP or a MMBP and then becomes the arrival of the next hop, which is beneficial to engineering implementation. The novel delay evaluation metrics, E2E packet delay and delay violation probability, are developed to assess the performance of SFC deployment. We formulate the SFC deployment as an integral linear programming (ILP) problem with the objective of minimizing the total cost. Finally, a heuristic algorithm called hop-by-hop bandwidth allocation and SFC deployment (HBASD) is designed to solve this problem. Simulation results show that compared with the up-to-date methods, our algorithm can guarantee the QoS requirements of E2E delay for services and save resources.

End-to-end performance assessment of a 3D network for 6G connectivity on Mars surface

Space Agencies from all over the world are planning human missions on the Red planet in the next 20–30 years. The landing of astronauts and their sojourn on the Martian surface will impose the presence in situ of some basic supporting infrastructures. Recent research by NASA highlighted the urgent necessity of providing efficient and readily-available wireless connection on the Martian surface, as well as long-haul connection to Earth. Thus, to fulfill the former, the objective of this paper is to study and assess a flexible 6G-based 3D network solution for mobile connectivity on Mars. 6G is going to provide guaranteed Quality-of-Service (QoS) for heterogeneous applications, while optimizing the use of the network resources. The Radio Access Network (RAN) of such an infrastructure will be fully softwarized together with the Next Generation Core (NGC). 6G 3D networks will employ drones, small satellites and orbiters due to the reduced distances between them, which can support low-latency wireless links. Moreover, rovers, landers and humans are regarded as end users of the system. An in-depth analysis regarding trade-offs to be accounted, when selecting a specific orbital altitude is detailed. Intensive end-to-end (E2E) emulation trials in OpenAirInterface (OAI) environment is carried out to test the feasibility of the whole network. The performance is evaluated by means of metrics such as E2E delay, packet loss and throughput. Finally, computational complexity and memory usage is estimated for each node of the proposed architecture.

Cooperative Resource Scheduling for Time-Sensitive Services in an Integrated XGS-PON and Wi-Fi 6 Network

10-Gbps symmetrical passive optical network (XGS-PON) and Wi-Fi 6 are two key technologies to provide gigabit access for the fifth-generation fixed network (F5G). However, how to integrate XGS-PON and Wi-Fi 6 to meet F5G’s stringent quality of service requirements is still a challenge. In this letter, we propose a cooperative resource scheduling scheme, in which a communication tunnel is established to achieve a low end-to-end (E2E) delay by sharing medium access control information between XGS-PON and Wi-Fi 6. Simulation results show that the proposed scheme can significantly reduce the E2E delay for time-sentinel services by up to 50% without sacrificing the performance of non-time-sensitive services.

An Effective Approach for Controller Placement in Software-Defined Internet-of-Things (SD-IoT).

The Software-Defined Networking (SDN) paradigm has transferred network intelligence from network devices to a centralized controller. Controllers are distributed in a network to eliminate a single point of failure (SPOF) and improve reliability and balance load. In Software-Defined Internet of Things (SD-IoT), sensors exchange data with a controller on a regular basis. If the controllers are not appropriately located in SD-IoT, the E2E latency between the switches, to which the sensors are connected, and the controller increases. However, examining the placement of controllers in relation to the whole network is not an efficient technique since applying the objective function to the entire network is a difficult operation. As a result, segmenting the network into clusters improves the efficiency with which switches are assigned to the controller. As a result, in this research, we offer an effective clustering strategy for controller placement in SDN that leverages the Analytical Network Process (ANP), a multi-criteria decision-making (MCDM) scheme. The simulation results demonstrated on real Internet topologies suggest that our proposed method outperforms the standard k-means approach in terms of E2E delay, controller-to-controller (C2C) delay, the fair allocation of switches in the network, and the communication overhead.

Advanced Cryptographic Standards-Based Secure Data Protocol for Distributed Data Storage and Communication in the Cloud

In this research, an ACS-based secure data protocol (ACS-based secure data protocol) is introduced for distributed data storage and communication in cloud. The component is constructed using the Owner’s Machine (OM), Data Processing Section (DPS), Cloud Monitoring Server (CMS), Metadata table, Key Management Server (KMS) and Receiver’s Machine (RM). The session key is generated by exchanging the data between the client and server using the mathematical operations, such as interpolation, hashing, Walsh transform and Elliptic curve cryptography. The Triple Data Encryption Algorithm (3DES) is used for performing the activities, like assigning index, uploading and slicing file and encrypting the sliced files. The fuzzy cluster-based mechanism and the angular distance are performed for indexing and retrieval. The metrics, such as E2E delay, time and detection rate are used for evaluating the developed ACS based secure data protocol in the presence of inside attack, password spoofing attack and Denial-of-Service (DoS) attack.

Deep-Learning-Aided Packet Routing in Aeronautical Ad Hoc Networks Relying on Real Flight Data: From Single-Objective to Near-Pareto Multiobjective Optimization

Data packet routing in aeronautical ad-hoc networks (AANETs) is challenging due to their high-dynamic topology. In this paper, we invoke deep learning (DL) to assist routing in AANETs. We set out from the single objective of minimizing the end-to-end (E2E) delay. Specifically, a deep neural network (DNN) is conceived for mapping the local geographic information observed by the forwarding node into the information required for determining the optimal next hop. The DNN is trained by exploiting the regular mobility pattern of commercial passenger airplanes from historical flight data. After training, the DNN is stored by each airplane for assisting their routing decisions during flight relying solely on local geographic information. Furthermore, we extend the DL-aided routing algorithm to a multi-objective scenario, where we aim for simultaneously minimizing the delay, maximizing the path capacity, and maximizing the path lifetime. Our simulation results based on real flight data show that the proposed DL-aided routing outperforms existing position-based routing protocols in terms of its E2E delay, path capacity as well as path lifetime, and it is capable of approaching the Pareto front that is obtained using global link information.

Two-Stage Task Offloading Optimization With Large Deviation Delay Analysis in IoT Networks

In the edge computing Internet of Things network, we minimize the offloading overhead (caused by the bandwidth cost for data transmission and computation resource consumption for task remote processing) while providing the end-to-end (E2E) delay provisioning. Under the scenario, a tandem queue consisting of a transmission queue and a computing process queue is formed by the tasks offloaded to the edge server via wireless link and then processed through the computing resource. Due to the tandem queue, the offloading decision and computing resource allocation are coupled over the tandem queue. To make the problem tractable, we decouple the above two operations and propose a two-stage offloading filtering and computing resource allocation policy. After decouple, we then investigate the delay bound violation probability of the tandem queue by leveraging large deviation analysis. Further, we reveal that under the same E2E delay provisioning, the offloading overhead under the proposed decoupled policy can approach to the non-decoupled optimum by selecting an appropriate value of control parameter. Simulation results verify the theoretical analysis and show the efficiency of the proposed policy.

Fuzzy logic based cross-layer design to improve Quality of Service in Mobile ad-hoc networks for Next-gen Cyber Physical System

5G standard by 3GGP has provision for Device-to-Device (D2D) communication over a Wireless Mobile Ad-hoc Network (MANET) framework. Recent research and development in 6G Networks and beyond has support for integration of MANET to the Mobile communication infrastructure to cater services to many potential future-proof applications like Smart Vehicular Networks using Internet of Vehicles (IoV) and Flying Ad-hoc Networks (FANET) for drone networks and military Ad-hoc networks. MANET being an Ad-hoc and infrastructure-less network poses major deployment challenge in resource allocation and management to facilitate strict Quality of Service (QoS) requirements for future Internet of Things (IoT) based Next-generation Cyber Physical System (NG-CPS). Most of MANETs use Contention-based Distributed Coordination Function (DCF) random Access Media Access Control (MAC) and a generic TCP/IP stack implementation. It is a daunting task to have deterministic model of network parameters for specific QoS requirements of IoT applications hence a soft-computing approach would be most viable solution considering network parameters across all five layers of TCP/IP stack that is a Cross-Layer design approach to improve QoS. In this paper, we have proposed a Fuzzy Logic system based Cross-Layer (FLS-CL) design for MANET to improve Network QoS parameters like Throughput, Packet Delivery ration (PDR) and End-to-End (E2E) delay. The proposed system has been implemented using Fuzzy Logic based parameters modeling using MATLAB and the Network simulation study using QualNet® simulator. The results are promising with average 27.64 % improvement in PDR and 76.04 % less E2E delay for connection-less UDP-based CBR applications and 3.28 % improvement in PDR and 58.81 % less E2E delay for connection-oriented TCP-based FTP applications. The QoS improvements are achieved with proposed FLS-CL as compared to state-of-the-art IEEE 802.11 based MANET without any FLS cross-layer optimization.

Data Dissemination in VANETs Using Clustering and Probabilistic Forwarding Based on Adaptive Jumping Multi-Objective Firefly Optimization

Data dissemination in a VANETs network requires a meticulous process to ensure a high quality of service and eliminate hazardous conditions due to congestion or a broadcast storm. Considering multi-metric approaches and their implicit conflicting nature, it is necessary to handle this through effective multi-objective optimization algorithms. An effective optimization can be handled using a meta-heuristic approach with a high level of solution interactions. For this purpose, firefly was selected, which is a type of meta-heuristic search algorithm. Several developments of the firefly optimization were added to increase its capability to find more dominating solutions, namely, objective decomposition, archive management, and controlled mutation for exploration and exploitation balance. This developed multi-objective optimization was designated as adaptive jumping multi-objective firefly algorithm (AJ-MOFA). Afterwards, AJ-MOFA was integrated with a clustering and forwarding mechanism (CFM). This mechanism includes three main components. The first is clustering, which uses arbitration based on the cluster head score; the second is a forwarding mechanism that uses probabilistic forwarding and the third is AJ-MOFA. The solution space design in CFM combined two variables: the first is the probability of forwarding and the second is the maximum number of nodes within one cluster. The metrics to be incorporated in the multi-objective optimizations are the packet delivery ratio (PDR), the end-to-end delay (E2E-delay) and the number of dropped packets. Comparing both AJ-MOFA and CFM with benchmarks using multi-objective optimization and networking metrics reveals the superiority in most evaluation measures, which makes them promising algorithms for data dissemination in VANETs. The results showed an accomplished PDR of 60% and an E2E delay of 6.6 seconds, while the number of dropped packets was almost nine for the entire running time of the experiment, comparing a similar or lower performance of the benchmarks for these metrics.

Adaptive mobility-aware and reliable routing protocols for healthcare vehicular network.

Healthcare vehicles such as ambulances are the key drivers for digital and pervasive remote care for elderly patients. Thus, Healthcare Vehicular Ad Hoc Network (H-VANET) plays a vital role to empower the digital and Intelligent Transportation System (ITS) for the smart medical world. Quality of Service (QoS) performance of vehicular communication can be improved through the development of a robust routing protocol having enhanced reliability and scalability. One of the most important issues in vehicular technology is allowing drivers to make trustworthy decisions, therefore building an efficient routing protocol that maintains an appropriate level of Quality of Service is a difficult task. Restricted mobility, high vehicle speeds, and continually changing topologies characterize the vehicular network environment. This paper contributes in four ways. First, it introduces adaptive, mobility-aware, and reliable routing protocols. The optimization of two routing protocols which are based on changing nature topologies of the network used for vehicular networks has been performed, amongst them, Optimized Link State Routing (Proactive) and Ad-hoc on Demand Distance Vector (Reactive) are considered for Packet Delivery Ratio (PDR) and throughput. Furthermore, Packet Loss Ratio (PLR), and end-to-end (E2E) delay parameters have also been calculated. Second, a healthcare vehicle system architecture for elderly patients is proposed. Third, a Platoon-based System model for routing protocols in VANET is proposed. Fourth, a dynamic channel model has been proposed for the vehicle to vehicle communication using IEEE8011.p. To optimize the QoS, the experimental setup is conducted in a discrete Network Simulator (NS-3) environment. The results reveal that the AODV routing protocol gives better performance for PDR as well as for PLR and the communication link established is also reliable for throughput. Where OLSR produces a large average delay. The adoptive mobility-aware routing protocols are potential candidates for providing Intelligent Transportation Systems with acceptable mobility, high reliability, high PDR, low PLR, and low E2E delay.

End-to-End Delay Bound for Wireless uVR Services Over 6G Terahertz Communications

The forthcoming sixth-generation (6G) network technology will trigger tremendous changes across several application scenarios and even in the way we work, communicate, and, more in general, organize our everyday life. In particular, in such a new digital era, virtual reality (VR) technology will play a fundamental role, carrying with it numerous challenges as regards the increasing demand of high rate, highly reliable, and low-latency communications, especially in reference to Internet-of-Things environments. In this sense, an effective end-to-end (e2e) delay analysis becomes imperative to pursue an efficient design of the foreseen VR services. Toward this goal, this article proposes the e2e delay investigation through the martingale theoretical bound and considering the stochastic network calculus principles for its formulation. The performance discussion focuses on the achieved communications reliability, comparing the analytical predictions obtained via the martingale bound with the simulation results, and the Markov queuing theory-based alternative. The presented results confirm the validity of the proposed approach, exhibiting noticeable closeness between the theoretical bound and the simulation outcomes.

MAC protocol with grouping awareness GMAC for large scale Internet-of-Things network.

The development of Medium Access Control (MAC) protocols for Internet of Things should consider various aspects such as energy saving, scalability for a wide number of nodes, and grouping awareness. Although numerous protocols consider these aspects in the limited view of handling the medium access, the proposed Grouping MAC (GMAC) exploits prior knowledge of geographic node distribution in the environment and their priority levels. Such awareness enables GMAC to significantly reduce the number of collisions and prolong the network lifetime. GMAC is developed on the basis of five cycles that manage data transmission between sensors and cluster head and between cluster head and sink. These two stages of communication increase the efficiency of energy consumption for transmitting packets. In addition, GMAC contains slot decomposition and assignment based on node priority, and, therefore, is a grouping-aware protocol. Compared with standard benchmarks IEEE 802.15.4 and industrial automation standard 100.11a and user-defined grouping, GMAC protocols generate a Packet Delivery Ratio (PDR) higher than 90%, whereas the PDR of benchmark is as low as 75% in some scenarios and 30% in others. In addition, the GMAC accomplishes lower end-to-end (e2e) delay than the least e2e delay of IEEE with a difference of 3 s. Regarding energy consumption, the consumed energy is 28.1 W/h for GMAC-IEEE Energy Aware (EA) and GMAC-IEEE, which is less than that for IEEE 802.15.4 (578 W/h) in certain scenarios.