IEEE has standardized the 802.15.4e Time Slotted Channel Hopping (TSCH) mode to provide stringent latency, higher reliability, and low duty-cycle in various Internet of Things (IoT) applications. TSCH eliminates interference and multi-path fading on channels, but its channel hopping feature severely affects the 6TiSCH (IPv6 over IEEE 802.15.4e TSCH mode) network formation. Further, 6TiSCH Minimal Configuration standard does not provide sufficient bandwidth (i.e., minimal cell) for quick transmission of control packets required by the new nodes (i.e., pledges) during their network association. Many works have been proposed on 6TiSCH network formation as it has high impact on network performance and lifetime. However, the existing works either did not use all the available physical channels while allocating minimal cell(s) or are not stable with topology changes. Therefore, this work proposes aTime-VariantRGB(TRGB) model for minimal cell allocation and scheduling, which results in faster association of pledges and maintains network stability. We evaluate the TRGB using Markov Chain model and also on a real 60-node testbed in FIT IoT-LAB. Testbed results show that TRGB achieves 51% and 23% improvement over the state-of-the-art scheme in terms of joining time and energy consumption, respectively, while maintaining stability of the network.

Routing Protocol for Low Power and Lossy Networks (RPL) is the de-facto routing standard for Internet of Things (IoT) applications. It has been designed to work with resource-constrained devices in constrained environment. In RPL, objective functions (OFs) play the role of selecting optimal paths. However, the existing OFs are not suitable for Mission Critical IoT (MC-IoT) applications. MC-IoT applications expect that the data should reach the destination within a strict deadline. So, reliability and delay are the two significant requirements in such type of applications. An existing work RMP-RPL achieves the hard reliability requirement for MC-IoT applications. However, it did not consider the delay requirement. Also, it was not tested for different traffic rates. Therefore, this paper proposes a reliable and delay-efficient multi-path RPL (RDMP-RPL) that optimizes both reliability and delay. It considers buffer and channel loss probabilities while calculating reliability. For delay calculation, it considers queueing and link delays. In addition, the protocol presents a method to select backup parents to meet end-to-end delay requirements. The results demonstrate that RDMP-RPL maintains a packet delivery ratio (PDR) of at least 99% and at most one second end-to-end delay (EED) considering a maximum of 5 hops for a packet to reach the destination from any of the source nodes for grid topology. But, for random topology, the number of hops can exceed 5. RDMP-RPL cannot achieve the strict requirements in situations where traffic rate, mobility and number of nodes cross a specific threshold. However, it outperforms other benchmark protocols by a significant margin.

Mission-critical Internet of Things (MC-IoT) applications span from the industrial field to the battlefield and from smart homes to healthcare. Reliability is one of the stringent requirements of such applications. Routing in low-power and Lossy Networks (RPL) is a standard routing protocol traditionally used in IoT applications. Unlike the traditional single-path-based RPL, the reliable multi-path RPL (RMP-RPL) selectskparents for each transmitting node to achieve the hard reliability requirement in MC-IoT applications. However, the RMP-RPL fails to achieve the reliability requirement when the number of source nodes and traffic rate increases. In this paper, a multi-path game theoretic congestion control (GTMP-RPL) approach is proposed on top of the RMP-RPL to reduce congestion at the parent nodes of any child. In case of congestion at any one of the selectedkparents, its child node replaces the congested parent by a non-congested parent with minimum rank from the set of remaining nodes. The rank of a node is calculated based on the Data Packet Drop Ratio (DPDR), Expected Transmission Count (ETX), and Node Mobility (NM) of that node. If no non-congested parent is available for that child node, a non-cooperative game is played among siblings to adjust their data transmission rates based on congestion occurrence at the parent, energy spent by the child, and parent connectivity of the child node. The solution obtained for the proposed game, using the Lagrange multiplier and Karush-Kuhn-Tucker (KKT) conditions, is used to reduce congestion at the parent node. The proposed scheme is validated using the cooja simulator in Contiki OS. Simulation results show that GTMP-RPL achieves a 99% packet delivery ratio for at most 50 source nodes with a traffic rate of 30 pkts/min present in a random topology of 101 nodes. In addition, it outperforms the other benchmark schemes by a significant margin to achieve hard reliability.

The 6TiSCH communication architecture provides delay-bounded packet delivery, energy efficient, and reliable data-delivering communication in mission-critical Internet of Things (IoT) applications. It uses IETF’s 6TiSCH minimal configuration (6TiSCH-MC) standard for resource allocation during network formation and routing using a routing protocol for low power and lossy network (RPL) as routing protocol. In RPL, the DODAG information solicitation (DIS) control packet is used to solicit routing information from the existing networks. However, it is observed that malicious transmission of this DIS packet can severely affect the 6TiSCH networks in terms of nodes’ network joining time and energy consumption. Therefore, designing countermeasures of DIS attack in 6TiSCH network has become critically important. Additionally, the existing works neither considered all the possible parameters together for detecting DIS attack nor energy efficient, and create control packet overhead. In this work, we model noncooperative gaming to determine the optimal probability of responding to a DIS packet. Subsequently, we design a trust model to detect malicious DIS transmission in 6TiSCH networks. Finally, we merge both the proposed gaming model and trust model to propose a scheme—gaming and trust-based countermeasure (GTCM) to reduce the effect of DIS attack in 6TiSCH networks. We implement the GTCM on Contiki-NG and validate it using open source FIT IoT-LAB testbed. Our experimental testbed results show that GTCM reduces the effect of DIS attack in terms of pledges’ (new nodes) joining time and energy consumption significantly.

The 6TiSCH communication architecture is widely used in Industrial Internet of Things (IIoT) to provide reliable, delay-bounded, and energy-efficient communication in multihop scenarios. However, the channel hopping feature and the resource allocation strategy of 6TiSCH minimal configuration (6TiSCH-MC) standard negatively impact the 6TiSCH network by increasing network formation time. 6TiSCH-MC allows only one cell (known as minimal cell) per slotframe to transmit control packets. When the number of joined nodes increases in the network, the formation time also increases because of the increasing congestion in the minimal cell. Furthermore, the existing works did not study the effect of transmission rates of all control packets together during 6TiSCH network formation. Therefore, in this work, a noncooperative game is formulated, for optimal transmission of control packets by the joined nodes. The obtained solution of the proposed game, using the Lagrange multiplier and Karush–Kuhn–Tucker (KKT) conditions, is used in the proposed congestion control scheme—game theory-based congestion control (GTCC). GTCC calculates the slotframe window (SW) size for every node to control the congestion in minimal cell without any signaling overhead. GTCC is validated using the analytical model as well as the FIT IoT-LAB testbed. The findings of both the analytical and testbed experiments show that GTCC significantly reduces the joining time and energy consumption of new nodes (i.e., pledges) as compared to previous benchmark schemes.

The IPv6 over IEEE 802.15.4e TSCH mode (6TiSCH) network is intended to provide reliable and delay bounded communication in multi-hop and scalable Industrial Internet of Things (IIoT). The IEEE 802.15.4e Time Slotted Channel Hopping (TSCH) link layer protocol allows the nodes to change their physical channel after each transmission to eliminate interference and multi-path fading on the channels. However, due to this feature, new nodes (aka pledges) take more time to join the 6TiSCH network, resulting in significant energy consumption and inefficient data transmission, which makes the communication unreliable. Therefore, the formation of 6TiSCH network has gained immense interest among the researchers. To date, numerous solutions have been offered by various researchers in order to speed up the formation of 6TiSCH networks. This article briefly discusses about the 6TiSCH network and its formation process, followed by a detailed survey on the works that considered 6TiSCH network formation. We also perform theoretical analysis and real testbed experiments for a better understanding of the existing works related to 6TiSCH network formation. This article is concluded after summarizing the research challenges in 6TiSCH network formation and providing a few open issues in this domain of work.

6TiSCH standardization helps the Industrial Internet of Things (IIoT) to achieve reliable and timed data delivery. It also deals with minimal resource allocation during network formation. However, faster network formation using minimum resources remains an active research issue. 6TiSCH minimal configuration standard (6TiSCH-MC) recommends to use only one cell per slotframe known as the minimal cell for all the nodes to transmit their network bootstrapping traffic. It is observed that, including 6TiSCH-MC, the existing schemes did not use all the available cells, and so, all the physical channels at the timeslot where this minimal cell resides, i.e., at timeslot zero. It results in underutilization of channel resources, and thus, higher network formation time. To leverage the available cells at timeslot zero of each slotframe, and thus to improve the network formation performance, an autonomous allocation and scheduling of minimal cell (TACTILE) is proposed. The main challenge is to utilize the available cells at timeslot zero as there is a minimal cell already scheduled for network bootstrapping. To address this issue, TACTILE distributes the location of the minimal cell as per nodes' EUI64 addresses along the different physical channels followed by scheduling them intelligently to avoid de-synchronization among nodes. Combined with Markov chain-based theoretical analysis, evaluation of TACTILE is done on the FIT IoT-LAB real testbed. The testbed results show that TACTILE can achieve 87% and 42% improvements in terms of joining time and energy consumption, respectively, compared to 6TiSCH-MC.

The IPv6 over the TSCH mode of IEEE 802.15.4e (6TiSCH) Working Group released 6TiSCH minimal configuration (6TiSCH-MC) standard for 6TiSCH network bootstrapping. 6TiSCH-MC allocates only one shared cell per slotframe, known as a minimal cell, to transmit all types of control packets. Our Markov Chain-based probabilistic analysis reveals that few network parameters have a high impact on the performance of 6TiSCH network formation due to increasing congestion in the minimal cell with the increased number of nodes. This work aims to improve the 6TiSCH network formation process by reducing congestion in the minimal cell. For this, the Trickle algorithm, which is used for controlling the rate of routing information-carrying packet transmission is modified so that sufficient routing information can be provided without congesting the minimal cell. To reduce the congestion further, a slotframe window (SW)-based adaptive scheme is proposed by which nodes are restricted to transmit their control packets frequently. The proposed dynamic Trickle algorithm and SW-based scheme are implemented on Contiki-NG and evaluated using FIT IoT-LAB testbed. The experimental results show that both the proposed schemes together improve the joining time and energy consumption of the pledges compared to the state-of-the-art schemes. Additionally, both the proposed schemes provide fair control packet transmission opportunities among the nodes in a network.

Industrial applications of Internet of Things (IoT) demand high reliability, deterministic latency, and high scalability with energy efficiency to the communication and networking protocols. 6TiSCH is a time slotted channel hopping (TSCH) medium access control (MAC) protocol running under the IPv6 enabled higher layer protocols for industrial IoT (IIoT). In this paper, we theoretically analyze the network formation protocol in 6TiSCH network. Analysis reveals that the performance of the 6TiSCH network degrades when a pledge (new node) joins as it increases channel congestion by allowing to transmit beacon message. On the other hand, beacon transmission is essential to expand or reorganize the present network topology. To overcome this performance tradeoff, a channel condition based dynamic beacon interval (C2DBI) scheme is proposed in which beacon transmission interval varies with channel congestion status during network formation. Channel congestion status is estimated by each joined node in distributed manner, and subsequently changes its beacon generation interval to best fit with present condition. Finally the performance of C2DBI is compared with the minimal configuration standard and few other benchmark protocols. Analytical, simulation and real testbed results show that the proposed scheme outperforms the state of the art protocols in terms of joining time and energy consumption during network formation.

Network bootstrapping is one of the initial tasks executed in any wireless network such as Industrial Internet of Things (IIoT). Fast formation of IIoT network helps in resource conservation and efficient data collection. Our probabilistic analysis reveals that the performance of 6TiSCH based IIoT network formation degrades with time because of the following reasons: (i) IETF 6TiSCH Minimal Configuration (6TiSCH-MC) standard considered that beacon frame has the highest priority over all other control packets, (ii) 6TiSCH-MC provides minimal routing information during network formation, and (iii) sometimes, joined node can not transmit control packets due to high congestion in shared slots. To deal with these problems, this article proposes two schemes—opportunistic priority alternation and rate control (OPR) and opportunistic channel access (OCA). OPR dynamically adjusts the priority of control packets and provides sufficient routing information during network bootstrapping, whereas OCA allows the nodes having urgent packet to transmit it in less time. Along with the theoretical analysis of the proposed schemes, we also provide comparison-based simulation and real testbed experiment results to validate the proposed schemes together. The received results show significant performance improvements in terms of joining time and energy consumption.

In mobile cloud computing (MCC), optimal utilization of resources (e.g., bandwidth), while maintaining the required level of quality-of-services (QoS), is essential. A user participating in the resource allocation process can provide untruthful information for acquiring undue advantages with respect to the allocated resource amount, and the cost incurred. In this paper, we identify, formulate, and address the problem of such misbehaviour. We formulate the bandwidth distribution as a constrained convex utility maximization problem, and solve it using the proposed cheating-resilient bandwidth distribution (CRAB) scheme. Numerical analysis shows that, in CRAB, the misbehaving user is impelled to behave normally as the misbehaviour increases its own cost while the other users including the cloud service provider (CSP) get benefit in terms of revenue. We investigate the existence of Nash Equilibrium (NE) of the proposed scheme. Both the problem and the solution are extensively analysed theoretically. The maximum and minimum selling prices of bandwidth, and the optimal solution for individual user are computed using the method of Lagrange multiplier.

In mobile cloud networks (MCNs), a mobile user is connected with a cloud server through a network gateway, which is responsible for providing the required quality-of-service (QoS) to the users. If a user increases its service demand, the connecting gateway may fail to provide the requested QoS due to the overloaded demand, while the other gateways remain underloaded. Due to the increase in load in one gateway, the sharing of load among all the gateways is one of the prospective solutions for providing QoS-guaranteed services to the mobile users. Additionally, if a user misbehaves, the situation becomes more challenging. In this paper, we address the problem of QoS-guaranteed secured service provisioning in MCNs. We design a utility maximization problem for quality-assured secured load sharing (QuaLShare) in MCN, and determine its optimal solution using auction theory. In QuaLShare, the overloaded gateway detects the misbehaving gateways, and, then, prevents them from participating in the auction process. Theoretically, we characterize both the problem and the solution approaches in an MCN environment. Finally, we investigate the existence of Nash Equilibrium of the proposed scheme. We extend the solution for the case of multiple users, followed by theoretical analysis. Numerical analysis establishes the correctness of the proposed algorithms.

We consider the problem of anomaly detection in network traffic. It is a challenging problem because of high-dimensional and noisy nature of network traffic. A popularly used technique is subspace analysis. Principal component analysis (PCA) and its improvements have been applied for subspace analysis. In this work, we take a different approach to determine the subspace, and propose to capture the essence of the traffic using the eigenvectors of graph Laplacian, which we refer as Laplacian components (LCs). Our main contribution is to propose a regression framework to compute LCs followed by its application in anomaly detection. This framework provides much flexibility in incorporating different properties into the LCs, notably LCs with sparse loadings, which we exploit in detail. Furthermore, different from previous work that uses sample graphs to preserve local structure, we advocate modelling with a dual-input feature graph that encodes the correlation of the time series data and prior information. Therefore, the proposed model can readily incorporate the 'physics' of some applications as prior information to improve the analysis. We perform experiments on volume anomaly detection using only link-based traffic measurements. We demonstrate that the proposed model can correctly uncover the essential low-dimensional principal subspace containing the normal Internet traffic and achieve outstanding detection performance.

In target tracking applications of wireless sensor networks (WSNs), one of the important but overlooked issues is the estimation of mobility behavior of a target inside a coverage hole. The existing approaches are restricted to networks with effective coverage by wireless sensors. Additionally, those works implicitly considered that a target does not change its mobility pattern inside the entire tracking region. In this paper, we address the above lacunae by designing a stochastic learning weak estimation-based scheme, namely mobility prediction inside a coverage hole (MIRACLE). The objectives of MIRACLE are two fold. First, one should be able to correctly predict the mobility pattern of a target inside a coverage hole with low computational overhead. Second, if a target changes its mobility pattern inside the coverage hole, the proposed estimator should give some estimation about all possible transitions among the mobility models. We use the trajectory extrapolation and fusion techniques for exploring all possible transitions among the mobility models. We validate the results with simulated traces of mobile targets generated using network simulator NS-2. Simulation results show that MIRACLE estimates the mobility patterns inside coverage hole with an accuracy of more than 60% in WSNs.

The IEEE 802.11e enhanced distributed channel access (EDCA) protocol follows class-based service differentiation for providing differentiated quality-of-service (QoS). However, its collision avoidance mechanism using backoff algorithm can be inefficient for providing improved performance with respect to throughput and channel access delay, especially in a high network configuration (i.e. number of stations) with imperfect wireless channel. The existing and emerging works have devoted considerable attention on tuning the backoff parameters for achieving optimal throughput only. The prior works do not consider the channel access delay and throughput metrics altogether for performance improvement. Additionally, in most of the cases, the optimal configuration of backoff parameters are performed by a centralized controller. In this paper, we propose a delay-aware distributed dynamic adaptation of contention window scheme, namely D2D, for the cumulative improvement of both the throughput and the channel access delay at runtime. The D2D scheme requires two ad-hoc, distributed, and easy-to-obtain estimates-delay deviation ratio and channel busyness ratio-of the present delay level and channel congestion status of the network, respectively. A key advantage of the D2D scheme is that it is compliant with the IEEE 802.11 standard, and, thus, can be seamlessly integrable with the existing wireless card. We show the integrated model of the medium access control protocol, namely D2D Channel Access (D2DCA), for the IEEE 802.11e networks. We further propose a two-dimensional Markov chain model of the D2DCA protocol for analyzing its theoretical performance in saturated networks with imperfect wireless channel. Theoretical comparison with the benchmark protocols establishes the effectiveness of the D2DCA protocol.

Collision is imminent in wireless networks (WNs) capacitated with randomized distributed channel access. In such networks, the probability of frame drop (Pdrop) is greater than zero due to successive collisions with a finite retry limit m. The IEEE 802.11 DCF is one such widely accepted protocol used in wireless local area networks (WLANs). The objective of the work reported in this paper is to provide guaranteed channel access to colliding frames for avoiding successive collisions for any loss-sensitive application, and thus, increase network throughput under finite m. We propose the semi-distributed backoff (SDB) algorithm, which operates in two modes: S-mode and R-mode. The key idea of the SDB scheme is to perform receiver-side backoff, if a mobile station encounters collision even after performing the existing sender-side backoff procedures. Using the SDB scheme, we design Semi-DCF, a MAC protocol for WLANs, which performs opportunistic migration from random to deterministic backoff. Semi-DCF functions independent of m. This protocol exploits the collision detection capability of receivers for disseminating information on optimal backoffs to the contenders using signature vectors. An analysis of Semi-DCF using the 2D Markov chain, coupled with results of network simulation establishes its superior performance in WLANs.

Mobile cloud computing (MCC) improves the computational capabilities of resource-constrained mobile devices. On the other hand, the mobile users demand a certain level of quality-of-service (QoS) provisioning while they use services from the cloud, even if the interfacing gateway changes due to the mobility of the users. In this paper, we identify, formulate, and address the problem of QoS-guaranteed bandwidth shifting and redistribution among the interfacing gateways for maximizing their utility. Due to node mobility, bandwidth shifting is required for providing QoS-guarantee to the mobile nodes. However, shifting alone is not always sufficient for maintaining QoS-guarantee because of varying spectral efficiency across the associated channels, coupled with the corresponding protocol overhead involved with the computation of utility. We formulate bandwidth redistribution as a utility maximization problem, and solve it using a modified descending bid auction. In the proposed scheme, named as AQUM, each gateway aggregates the demands of all the connecting mobile nodes and makes a bid for the required amount of bandwidth. We investigate the existence of Nash equilibrium (NE) in the proposed solution. Theoretically, we deduce the maximum and minimum selling prices of bandwidth, and prove the convergence of AQUM. Simulation results establish the correctness of the proposed algorithm.

Body-sensors such as accelerometers, oximeters and arm cuff based monitoring systems are used to sense patients' health conditions. Any abnormal behavior of patient's data triggers an alert signal to the health-centers to take action. In this paper, we address the problem of mobile patients' health monitoring using Health-Cloud. When a patient changes his/her location from one place to another, the associated default gateway changes. With the change in the gateway connected to the health-cloud, the optimum mapping between the server and the mobile node also changes. We propose an optimal resource allocation framework for health-cloud to monitor patients' health conditions when they change locations. To optimize the resource allocation problem and provide an optimum mapping between the mobile node and the server, we use an auction theory based solution approach. We evaluate the performance of the proposed scheme numerically. The experimental results show that we receive 20%, 58%, and 61% more utility for the three different cases with respect to the default mapping.

Underwater sensor networks (UWSNs) can be deployed for sensing the environment in oceanographic columns and other water bodies in which they are deployed. The peculiar characteristic of the underwater medium, coupled with the queer nature of the sound waves in water, poses an enigmatic problem for UWSN researchers. In this study, the authors focus on the problem of UWSN jamming, which is a popular type of denial-of-service attack. The existing jamming detection solutions for sensor networks are primarily targeted towards the terrestrial ones. In this work, the authors study the unique characteristics of jamming in UWSN, and propose a protocol, known as underwater jamming detection protocol (UWJDP), to detect and mitigate jamming in underwater environments. The results show that if the packet delivery ratio (PDR) is less than or equal to 0.8, the authors have the maximum probability of detecting jamming. The jamming detection ratio is around 2–11% more for the said PDR.