MAC Scheduling Research Articles

Anti-Eavesdropping by Exploiting the Space–Time Coupling in UANs

Due to the space–time coupling access, we find that anti-eavesdropping opportunities exist in underwater acoustic networks (UANs), where packets can be successfully received only by the intended receiver, but collide at the unintended receivers. These opportunities are highly spatially dependent, and this paper studies the case that linearly deployed sensor nodes directly report data toward a single collector. We found an eavesdropping ring centered around these linearly deployed sensor nodes, where the eavesdropper could steal all the reported data. Since the typical receiving-alignment-based scheduling MAC (TRAS-MAC) will expose the relative spatial information among the sensor nodes with the collector, the eavesdropper can locate the eavesdropping ring. Although moving the collector into the one-dimensional sensor node chain can degrade the eavesdropping ring to a point that constrains the eavesdropping risk, the collector’s location will be subsequently exposed to the eavesdropper. To efficiently protect the reported data and prevent the exposure of the collector’s location, we designed a slotted- and receiving-alignment-based scheduling MAC (SRAS-MAC). The NS-3 simulation results showed the effectiveness of the SRAS-MAC and the TRAS-MAC in protecting data from eavesdropping, which protect 90% of the data from eavesdropping in the one-eavesdropper case and up to 80% of data from eavesdropping in ten-eavesdropper cases. Moreover, unlike TRAS-MAC, which will expose the collector’s location, SRAS-MAC provides multiple positions for the collector to hide, and the eavesdropper cannot distinguish where it is.

AS-MAC: An Adaptive Scheduling MAC Protocol for Reducing the End-to-End Delay in AUV-Assisted Underwater Acoustic Networks

AS-MAC: An Adaptive Scheduling MAC Protocol for Reducing the End-to-End Delay in AUV-Assisted Underwater Acoustic Networks

Performance Analysis of Sensing-based Semi-Persistent Scheduling (SB-SPS) MAC Protocol for C-V2X

Sensing-based Semi-Persistent Scheduling (SB-SPS) MAC protocol is proposed as part of the latest cellular vehicle to everything (C-V2X) standard for medium access between vehicles. As C-V2X uses LTE based frame structure, mode 4 of the C-V2X standard uses SB-SPS to allocate resource blocks effectively. C-V2X shows great potential for the future as it brings many improvements such as enhanced range, reliability, and the ability to support and evolve with emerging technologies such as 5G. In this article, the SB-SPS protocol’s performance was analyzed in different scenarios using OMNET++, SUMO, and Veins simulator. Different vehicle speeds and densities were used to observe the effect on packet loss and throughput. It was found that as packet loss decreased, throughput increased when the mobility of vehicles decreased. The effects of changing some important parameters of SB-SPS were also observed. The results showed that while parameters such as increasing the number of subchannels increased the packet delivery ratio (PDR), the change in the probability of resource reselection parameter did not affect the PDR.

A Multi-Path MAC Scheduling Scheme for Multi-Channel Wireless Sensor Networks.

Designing reasonable MAC scheduling strategies is an important means to ensure transmission quality in wireless sensor networks (WSNs). When there exist multiple available routes from the source to the destination, it is necessary to combine a data traffic allocation mechanism and design a multi-path MAC scheduling scheme in order to ensure QoS. This paper develops a multi-path resource allocation method for multi-channel wireless sensor networks, which uses random-access technology to complete MAC scheduling and selects the transmission path for each packet according to the probability. Through theoretical analysis and simulation experiments, it can be found that the proposed strategy can provide a reliable throughput capacity region. Meanwhile, due to the use of random-access technology, the computational complexity of the proposed algorithm can be independent of the number of links and channels.

APP-Aware MAC Scheduling for MEC-Backed TDM-PON Mobile Fronthaul

In the 5G era and beyond, new applications (APPs) have more stringent requirements for low latency. The cloud radio access network (C-RAN) with TDM-PON-based mobile fronthaul (MFH) and multi-access edge computing (MEC) has been regarded as an efficient architecture for serving latency-critical APPs. Many studies have focused on latency optimization issues in the MFH or MEC segment. However, the ultimate latency from the end-user’s perspective is end-to-end (E2E) latency, which includes the latency in both the MFH and MEC segments. When coordinating MFH with MEC, the E2E latency optimization may be mismatched and inefficient. To address this issue, we propose an APP-aware MAC scheduling scheme that allocates uplink time resources based on the MEC-backed conditions and APPs’ traffic dynamics. Accordingly, we introduce an AI-based traffic prediction approach to capture traffic fluctuations in various APPs. Simulations show that our proposed scheme improves the performances of latency violation ratio and average E2E latency by up to 30% and 8%, respectively.

System analysis of QoS schedulers for XR traffic in 5G NR

Fifth Generation New Radio (5G NR) presents a new framework for Quality-of-Service (QoS) management that especially fits cases for eXtended Reality (XR) traffic applications thanks to the new presented concept of QoS flows that can handle various service data flows. In that respect, in this paper we exploit the QoS flow model and we present a QoS MAC scheduler that can classify XR and mixed traffic based on the assigned QoS indicators to each traffic. We perform an end-to-end system level evaluation under two scenarios using the ns-3 5G-LENA simulator. First, we validate the correct operation of the QoS MAC scheduler in a single-cell scenario under non-saturation and saturation conditions. Then, we consider a realistic multi-cell scenario defined by the ITU-R and used for calibration of the 5G-LENA simulator, in order to evaluate the proposed solution and study its performance under realistic network conditions. Results demonstrate the correct functionality of the proposed QoS MAC scheduler and prove its ability to classify XR and other types of traffic based on the desired QoS indicators.

Q-learning based task scheduling and energy-saving MAC protocol for wireless sensor networkss

Q-learning based task scheduling and energy-saving MAC protocol for wireless sensor networkss

Research on Throughput-Guaranteed MAC Scheduling Policies in Wireless Networks.

In wireless networks, MAC scheduling methods can be divided into two types according to the implementation model: centralized and distributed scheduling. By reasonably designing MAC scheduling policies, both centralized and distributed schedulers can ensure a reliable throughput capacity region, i.e., realizing throughput-guaranteed. However, it can be found that some existing throughput-guaranteed scheduling schemes cannot further ensure bounded end-to-end average delay, and the reason for this phenomenon has not been deeply analyzed. In practical communication networks, throughput and delay are equally important. Based on this idea, the existing MAC scheduling strategies are investigated systematically in this paper from two aspects of throughput and delay, and their performances are evaluated and compared through both theoretical analysis and simulation experiments. The work of this paper provides a theoretical basis for the improvement of MAC scheduling technology in the next-generation wireless networks.

An energy aware cluster‐based routing and adaptive semi‐synchronized MAC for energy harvesting WSN

AbstractMedium access control (MAC) layer scheduling is an intelligent solution to protract the lifetime of energy harvesting wireless sensor network (WSN) which is challenging issue in recent times. Self‐adaptive MAC protocol was working upon reinforcement learning. However, this decentralized adaptive scheduling introduces collisions and degrades the overall network performance. To fix this problem, this paper proposes novel semi‐synchronized MAC approach for energy harvesting WSN. The major objective of this work is to improve energy efficiency of the network by minimizing energy consumption which is the major issue in WSN. Proposed WSN network is modeled with dual mobile sinks with circular moving path and static sensor nodes to monitor the environment. Our novel MAC approach is initiated with unequal cluster formation by correlation based unequal clustering scheme in which multi‐objective elephant herding optimization (CUC‐MEHO) algorithm is incorporated for cluster head (CH) selection. In clustered network, all sensor nodes follow semi‐synchronized adaptive active period MAC scheduling (S2A2MAC) protocol. In this work, S2A2MAC operates upon hidden Markov model (HMM) which controls the active time period of a node in an adaptive manner. Energy efficient hop‐by‐hop intra‐cluster routing is empowered by Bayes rule enabled perfect matching (BR‐PM) algorithm. Before route selection, all candidate nodes are regarded into perfect match, partially match, and no match nodes. Furthermore, emergency data is identified by CH based on flag value and transmitted without any time delay. For emergency data transmission, extremity aware routing (EAR) algorithm is presented and EAR algorithm is functioning on hopcount and distance criteria. Finally, proposed network is evaluated by extensive simulations in NS‐3.26. Simulation upshots show better performance in percentage of dead nodes, network lifetime, energy consumption, PDR, and delay.

Hybrid Beamforming in 5G mmWave Networks: A Full-Stack Perspective

This paper studies the cross-layer challenges and performance of Hybrid Beamforming (HBF) and Multi-User Multiple-Input Multiple-Output (MU-MIMO) in 5G millimeter wave (mmWave) cellular networks with full-stack TCP/IP traffic and MAC scheduling. While previous research on HBF and MU-MIMO has focused on link-level analysis of full-buffer transmissions, this work reveals the interplay between HBF techniques and the higher layers of the protocol stack. To this aim, prior work on the full-stack evaluation of mmWave cellular networks has been extended by including the modeling of MU-MIMO and HBF. Our results reveal novel relations between the networking layers and the HBF MU-MIMO performance at the physical layer. Particularly, throughput can be increased in 5G networks by means of Space Division Multiple Access (SDMA). However, in order to achieve such benefits it is necessary to take into account certain trade-offs and the implementation complexity of a full-stack HBF solution.

Scheduled Access Strategy for Improving Sensor Node Battery Life Time and Delay Analysis of Wireless Body Area Network

In WBAN, energy efficiency is a major concern. The sensor nodes attached to the human body are battery-powered devices with a finite lifespan. These sensor nodes assist in gathering biological data from the human body and transmitting it to a control device. In WBAN, the MAC protocol is critical in evaluating a protocol’s energy efficiency. Traditional MAC protocols aim to boost throughput and bandwidth efficiency. The most critical aspect is that they lack in energy conserving mechanism. By employing correct control techniques that aid in the efficient use of energy resources, the useful network life time can be extended. Several MAC protocols for WBAN have been devised to reduce energy consumption, and packet collision, idle listening, overhearing, and control packet overhead are the main causes of energy waste in wireless networks. Idle listening, packet overhead, overhearing, and collision rate are all addressed by the energy-saving technique. In WBAN, we introduced a novel energy-efficient MAC protocol called Scheduled Access MAC (SAMAC) to extend the network life time without sacrificing QoS. Using the Castalia simulator, we analyze and compare the performance of our proposed SAMAC to that of the BaselineMAC (IEEE 802.15.6) and ZigBeeMAC (IEEE 802.15.4) in terms of energy consumption, packet delivery ratio, and end-to-end delay. In terms of both energy conversion and WBAN Quality of Service, our simulation results suggest that our proposed SAMAC is more efficient than Baseline MAC and ZigBeeMAC.

Reinforcement Learning TDMA-Based MAC Scheduling in the Industrial Internet of Things: A Survey

As technology progresses, almost all Industrial Internet of Things applications are becoming more data-driven. Hence, more advanced ways of communication are required to both save energy and become efficient to collect huge amounts of data. Researchers have now agreed that the root improvement of IIoT communication can start from a lower layer which is Data Link. Time Division Medium Access-based protocols on this layer have drawn academia's attention to decrease the energy consumption of IIoT devices and achieve higher levels of throughput. Yet, a problem arises, that is, developing a scheduler has always been troublesome while designing a Medium Access Control protocol. Scheduling communication in TDMA-based MAC protocols is considered an NP-hard problem. It is one of the topics highly debated among researchers to make the scheduling adaptive to the huge variation of IIoT application requirements. Conventional scheduling algorithms may suffer from the rapid changes in sensor network topology, network throughput, and applications’ delay targets. Therefore, Reinforcement Learning algorithms are being integrated into scheduling techniques because of their adaptability and efficiency. This paper surveys RL-based TDMA MAC protocols and compares them in terms of several unified features. Each protocol is explained and discussed with others regarding its advantages and drawbacks.

Delay-Based Resource Allocation With Fairness Guarantee and Minimal Loss for eMBB in 5G Heterogeneous Networks

Heterogeneity is defined as one of the core merits in the 5th Generation (5G) mobile systems. Such a trait is prominent in modern 5G traffic scenarios, i.e., enhanced Mobile Broadband (eMBB), where coarse Quality of Service (QoS) profiles need to be satisfied over the shared transmission channel. For that, Radio Resource Management (RRM) became a challenging problem that should be figured out based on the traffic scenario. Extensive efforts dwelled in the literature attempt to solve the resource allocation problem in the downlink channel by maximizing the gain for a certain aspect in the QoS profile. This, however, poses a challenge for 5G-related traffic scenarios such that multi-dimension QoS shall be attainable. Therefore, in this paper, a Delay-aware Resource Allocation for Guaranteed Fairness and minimal Loss (DRAGFL) is proposed to enhance the QoS for Real-Time (RT) services in eMBB 5G Heterogeneous Networks. The ultimate objective of DRAGFL is to maintain a steadily low latency for delay-sensitive flows without restraining the service fairness and the data loss in the overload states. DRAGFL enhances the efficiency of the MAC layer scheduler throughout three phases. Firstly, generating delay-derived weight matrix of the resources blocks to radio bearers from eMBB different classes. Then, greedy-based flows prioritization for Resource Blocks (RBs) assignment. Finally, the data rate of the RT and Non RT (NRT) flows is further emphasized through a channel-aware principle that is invoked conditioning to the remaining radio resources and available data to be scheduled in the interval. The performance evaluation using system-level simulations reveals prominent gains of DRAGFL in sustaining a steadily low end-to-end delay in the high congestion states. Moreover, it maintains ideal states of service fairness with low data loss for different traffic loads to indicate a promising MAC scheduler for the developing scenarios of 5G.

Edge Intelligent Agent Assisted Hybrid Hierarchical Blockchain for continuous healthcare monitoring & recommendation system in 5G WBAN-IoT

Wireless Body Area Network (WBAN) is an emerging technology that faces many challenges for monitoring patient health state information and early diagnosis of any disease (e.g. COVID-19). In addition, WBAN has many issues such as high energy consumption, overhead and latency due to the scarcity in resources, for that we bring edge assisted 5G environment in WBAN. The patient information is sensitive and easily traced by the attackers due to insecurity, for that, we proposed the EiA-H2B model (Edge intelligent Agent Hybrid Hierarchical Blockchain) which includes five phases. Firstly we proposed Biological PUF based sensor authentication, which is a strong credential that provides high security. All the sensors are authenticated by the virtual authenticator that is deployed by a blockchain ledger. Due to the mobility of WBAN, we focused on handover that is done by Bi-Partite One to N matching theory. Secondly, we proposed high voting based virtual clustering, in this phase high voting sensor is elected as a super node and that is used to create a virtual cluster. Thirdly, we proposed duty cycle MAC scheduling protocol is used to predict the original state of the sensors which is done by Attention Matrix based Gated Recurrent Unit (AM-GRU), and then the timeslots are allocated for avoiding packet loss and retransmission. Fourth, we perform relay selection and routing that is done by Global Optimization based Artificial Electric Field Algorithm (AEFA). And finally, we predict emergency data and generate an alert in EiA using Human Learning aided State Action Reward State Action (SARSA) algorithm that finds the current state and predicts the corresponding action. Based on that current state information SARSA provides an efficient recommendation to the patients. Experiments are conducted by OMNeT ++ network simulator and evaluate the performance of the proposed EiA-H2B model in terms of energy consumption, success rate, network throughput, end to end delay, packet loss rate, authentication time and processing time.

Analysis of performance vulnerability of MAC scheduling algorithms due to SYN flood attack in 5G NR mmWave

Analysis of performance vulnerability of MAC scheduling algorithms due to SYN flood attack in 5G NR mmWave

Collision-free and low delay MAC protocol based on multi-level quorum system in underwater wireless sensor networks

Underwater wireless sensor network (UWSN) is a typical application of wireless network in underwater environment, which mainly uses acoustic communication at present. However, due to the characteristics of high bit error rate, very limited bandwidth and high transmission delay, the data transmission collision of underwater communication is very serious. In order to reduce transmission collision and improve network performance, we propose a collision-free time slot scheduling MAC protocol based on multi-level quorum system for high loaded UWSNs. The proposed protocol can allocate different time slots for nodes in the same collision area, while realize space reuse for nodes in different collision areas. Considering the unbalanced data transmission of each node, a multi-level quorum system algorithm is constructed for fairness, which can allocate time slots on demand according to the data transmission amount of each node. In order to ensure reliable transmission of data, a light weight retransmission mechanism is designed to reduce the impact of long delay on channel duty cycle. Simulation results prove that the proposed MAC protocol can effectively avoid transmission collision, reduce transmission delay, improve system energy efficiency, and have good adaptability for different network topologies.

Po-Fi: Facilitating innovations on WiFi networks with an SDN approach

Most of softwareized WiFi networks rely on dedicated softwares for realizing novel wireless functionalities. However, such an approach is not flexible enough, and introduces management complexity. On the other hand, the programmable forwarding pipeline, which models packet processing as multiple stages of forwarding rules, exhibits great flexibility in facilitating network innovations, and has been recognized as a consensus for abstracting SDN data plane. In this paper, we present Po-Fi, an architecture for software-defined WiFi networks. Based on Protocol-Oblivious Forwarding (POF), Po-Fi follows the SDN consensus by abstracting WiFi AP as a programmable forwarding pipeline, and provides a rich and unified programmability to enable user to realize novel wireless functionalities with forwarding rules. Comparing with previous approaches, Po-Fi is highly flexible in facilitating WiFi innovations. To show this, we realize a wide range of use cases with Po-Fi, including per-client virtual AP (VAP), seamless mobility, multi-AP MPTCP data transmission, smooth remote AP switching for wireless backhaul, and TDMA MAC scheduling. We implement a Po-Fi prototype with commodity hardware, and evaluate the use cases with real-world experiments. The results show that the Po-Fi facilitated innovations can effectively improve the WiFi network services.

Integration of Steerable Smart Antennas to IETF 6TiSCH Protocol for High Reliability Wireless IoT Networks

Steerable directional antennas are increasingly utilised to improve the overall performance of the traditional wireless sensor networks. Steerable directional antenna based networking solutions increase the network capacity by providing a longer range of transmission and reduced interference as compared to networking solutions with omni-directional antennas. However, the use of smart antennas requires complex algorithms and such algorithms may not be easily leveraged in low power Internet of Things (IoT) networks. This study presents mechanisms for integrating low complexity smart antenna solutions into IETF 6TiSCH protocol with the aim of creating scalable and reliable industrial IoT networks. The solution defines extensions to MAC layer and scheduling mechanisms of IETF 6TiSCH protocol to enable its seamless integration with low complexity steerable smart antennas. The results of this study show that smart antenna enabled 6TiSCH protocol stack outperforms the legacy 6TiSCH stack in terms of data delivery performance especially in high density scenarios.

Survey: energy efficient protocols using radio scheduling in wireless sensor network

An efficient energy management scheme is crucial factor for design and implementation of any sensor network. Almost all sensor networks are structured with numerous small sized, low cost sensor devices which are scattered over the large area. To improvise the network performance by high throughput with minimum energy consumption, an energy efficient radio scheduling MAC protocol is effective solution, since MAC layer has the capability to collaborate with distributed wireless networks. The present survey study provides relevant research work towards radio scheduling mechanism in the design of energy efficient wireless sensor networks (WSNs). The various radio scheduling protocols are exist in the literature, which has some limitations. Therefore, it is require developing a new energy efficient radio scheduling protocol to perform multi tasks with minimum energy consumption (e.g. data transmission). The most of research studies paying more attention towards to enhance the overall network lifetime with the aim of using energy efficient scheduling protocol. In that context, this survey study overviews the different categories of MAC based radio scheduling protocols and those protocols are measured by evaluating their data transmission capability, energy efficiency, and network performance. With the extensive analysis of existing works, many research challenges are stated. Also provides future directions for new WSN design at the end of this survey.

Pair‐based sink relocation and route adjustment in mobile sink WSN integrated IoT

In recent years, Wireless Sensor Network (WSN) have expanded as foundation infrastructure for Internet of Things (IoT). However, integrating WSN into IoT is a challenging task due to its poor network lifetime and high energy consumption. To address these shortcomings, our proposed work performs five sequential processes: Initially, we split the network region into multiple partitions using Quad Tree combined Binary Tree (QTcBT) partitioning algorithm. We carry out Weight based Cluster Head Selection (WCHS) method to select a cluster head in each partition. A novel Pair based Sink Relocation Scheme (PSRS) is proposed to relocate the sink node which effectually increases the network lifetime. We execute Destination Oriented Directed Acyclic Graph (DODAG) based route adjustment that adjusts route by considering three rules. Finally, we perform Type 2 Fuzzy based Adaptive MAC Scheduling (T2FAMS) that is handled by the cluster head. At last, we evaluate the performance of our proposed work in terms of metrics including Energy consumption, End to End delay, Network lifetime, Delivery success ratio and Number of nodes alive. From the evaluation, we conclude that our work reduces energy consumption up to 20% and improves network lifetime up to 30% compared to the existing QDVGDD and GR methods.