Joint Channel Assignment Research Articles

Q-CAR: an intelligent solution for joint QoS multicast routing and channel assignment in multichannel multiradio wireless mesh networks

Multicast routing improves the efficiency of a network by effectively utilizing the available network bandwidth. In multichannel multiradio wireless mesh networks the channel allocation strategy plays a vital role along with multicast tree construction. However, the multicast routing problem in multichannel multiradio wireless mesh networks is proven to be NP-hard. With this paper, we propose a Quality of Service Channel Assignment and multicast Routing (Q-CAR) algorithm. The proposed algorithm jointly solves the channel assignment and multicast tree construction problem by intelligent computational methods. We use a slightly modified differential evolution approach for assigning channels to links. We design a genetic algorithm based multicast tree construction strategy which determines a delay, jitter bounded low cost multicast tree. Moreover, we define a multi objective fitness function for the tree construction algorithm which optimizes interference as well as tree cost. Finally, we compare the performance of Q-CAR with QoS Multicast Routing and Channel Assignment(QoS-MRCA) and intelligent Quality of service multicast routing and Channel Assignment(i-QCA) algorithm in multichannel multiradio wireless mesh network (simulated) environments. Our experimental results distinctly show the outstanding performance of the proposed algorithm.

Joint channel assignment and routing protocol for cognitive radio ad hoc networks

Conventional single channel wireless ad hoc networks usually suffer from low network throughput owing to the higher number of packet transmissions required for multi-hop communication. Using multiple channels within a single network can improve the network throughput. In multi-channel communication networks, the channels must be assigned appropriately to maximise network performance. Existing channel assignment methods are usually based on the approach of interference reduction/minimisation, for example, by making a link to operate on only one channel and different links to operate on different channels. In this paper, we go in the opposite direction and propose to make links to operate on more channels. A new distributed joint channel assignment and routing protocol for cognitive radio ad hoc networks called cognitive radio-enhanced AOMDV is proposed. Simulation studies showed that our method outperforms other methods.

A joint routing and channel assignment in multi-radio multi-channel wireless mesh networks

To reduce inter-link interference and balance networks loads, this paper presents and evaluates a cross-layer algorithm for multi-radio multi-channel wireless mesh networks (WMNs), while conducting routing channel assignments. In channel assignment phase, we propose a greedy algorithm based on a multi-radio multi-channel interference model and select the channel with minimum of interference degree. In the routing phase, a new routing parameter which comprehensively considers interference, delay, load balancing and other factors is proposed. The new algorithm is compared with existing algorithm that is multi-radio multi-channel WMN based on ad hoc on-demand distance vector routing (MRMC-AODV) to illustrate the advantages. When the load reaches 6 Mbps, the throughput exceeds 14% of the MRMC-AODV, with a delay of nearly 80% of the MRMC-AODV latency and it reduces packet loss ratio by about 12%. The simulation results show that this algorithm can effectively improve the network throughput, reduce delay and decrease packet loss ratio.

A joint routing and channel assignment in multi-radio multi-channel wireless mesh networks

A joint routing and channel assignment in multi-radio multi-channel wireless mesh networks

A cross-layer optimization framework for joint channel assignment and multicast routing in multi-channel multi-radio wireless mesh networks

ABSTRACTExisting literature on multicast routing protocols in wireless mesh networks (WMNs) from the view point of the links involved in routing are divided into two categories: schemes are aimed at multicast construction with minimal interference which is known as NP hard problem. In contrast, other methods develop network-coding-based solutions with the main objective of throughput maximization, which can effectively reduce the complexity of finding the optimal routing solution from exponential to polynomial time. The proposed framework in this paper is placed in the second category. In multi-channel multi-radio WMNs (MCMR WMNs), each node is equipped with multiple radios, each tuned on a different channel. In this paper, for the first time, we propose a cross-layer convex optimization framework for joint channel assignment and multicast throughput maximization in MCMR WMNs. The proposed method is composed of two phases: in the first phase, using cellular learning automata, channels are assigned to the links established between the radios of the nodes in a distributed fashion such that the minimal interference coefficient for each link is provided. Then, the resultant channel assignment scheme is utilized in the second phase for throughput maximization within an iterative optimization framework based on Lagrange relaxation and primal problem decomposition. We have conducted many experiments to contrast the performance of our solution against many representative approaches.

Channel assignment, link scheduling, routing, and rate control for multi-channel wireless mesh networks with directional antennas

The wireless mesh network (WMN) has attracted significant interests as a broadband wireless network to provide ubiquitous wireless access for broadband services. Especially with incorporating multiple orthogonal channels and multiple directional antennas into the WMN, each node can communicate with its neighbor nodes simultaneously without interference between them. However, as we allow more freedom, we need a more sophisticated algorithm to fully utilize it and developing such an algorithm is not easy in general. In this paper, we study a joint channel assignment, link scheduling, routing, and rate control problem for the WMN with multiple orthogonal channels and multiple directional antennas. This problem is inherently hard to solve, since the problem is formulated as a mixed integer nonlinear problem (MINLP). However, despite of its inherent difficulty, we develop an algorithm to solve the problem by using the generalized Benders decomposition approach [2]. The simulation results show the proposed algorithm provides the optimal solution to maximize the network utility, which is defined as the sum of utilities of all sessions.

Coalition Formation Game Based Relay Selection and Frequency Sharing for Cooperative Relay Assisted Wireless D2D Networks with QoS Constraints

With device-to-device (D2D) communications, an inactive user terminal can be utilized as a relay node to support multi-hop communication so that connective experience of the cell-edge user as well as the capacity of the whole system can be significantly improved. In this paper, we investigate the spectrum sharing for a cooperative relay assisted D2D communication underlying a cellular network. We formulate a joint relay selection and channel assignment problem to maximize the throughput of the system while guaranteeing the quality of service (QoS) requirements of cellular users (CUs) and D2D users (DUs). By exploiting coalition formation game theory, we propose two algorithms to solve the problem. The first algorithm is designed based on merge and split rules while the second one is developed based on single user`s movement. Both of them are proved to be stable and convergent. Simulation results are presented to show the effectiveness of the proposed algorithms.

Joint multicast routing and channel assignment for multi-radio multi-channel wireless mesh networks with hybrid traffic

In this paper, joint multicast routing and channel assignment problem in wireless mesh networks (WMNs) with hybrid traffic is investigated. Previous works design routing and channel assignment schemes for WMNs with single multicast session, however, resource usage is optimized for only one multicast session in this case and overall network load balance is left out of consideration. This may result in high congestion in some links, while others are underutilized. In this paper, multicast routing and channel assignment problem is solved from traffic management perspective by introducing load balance. Programming formulation is formulated to obtain the optimal results which can be used as benchmark to evaluate other schemes. Multicast weighted conflict graph is designed to model partially overlapped channels (POCs) interference in hybrid traffic scene. It regards links originating from the same node as one transmission to fully exploit wireless broadcast advantage; it uses link weight to measure interference degree and gives full consideration to interference characteristics of POCs. A heuristic multicast routing and channel assignment scheme based on multicast weighted conflict graph is designed to solve the joint problem, and simulation results show that the heuristic scheme can reduce network interference and improve WMNs service capability while dramatically reducing computational complexity.

Joint Caching, Routing, and Channel Assignment for Collaborative Small-Cell Cellular Networks

We consider joint caching, routing, and channel assignment for video delivery over coordinated small-cell cellular systems of the future Internet. We formulate the problem of maximizing the throughput of the system as a linear program, in which the number of variables is very large. To address channel interference, our formulation incorporates the conflict graph that arises when wireless links interfere with each other due to simultaneous transmission. We utilize the column generation method to solve the problem by breaking it into a restricted master subproblem that involves a select subset of variables and a collection of pricing subproblems that select the new variable to be introduced into the restricted master problem, if that leads to a better objective function value. To control the complexity of the column generation optimization further, due to the exponential number of independent sets that arise from the conflict graph, we introduce an approximation algorithm that computes a solution that is within $\epsilon $ to optimality, at much lower complexity. Our framework demonstrates considerable gains in average transmission rate at which the video data can be delivered to the users, over the state-of-the-art Femtocaching system, of up to 46%. These operational gains in system performance map to analogous gains in video application quality, thereby enhancing the user experience considerably.

A Channel Assignment and Routing Algorithm for Energy Harvesting Multiradio Wireless Mesh Networks

Wireless mesh networks are being deployed all around the world both to provide ubiquitous connection to the Internet and to carry data generated by several services (video surveillance, smart grids, earthquake early warning systems, etc.). In those cases where fixed power connections are not available, mesh nodes operate by harvesting ambient energy (e.g., solar or wind power) and hence they can count on a limited and time-varying amount of power to accomplish their functions. Since we consider mesh nodes equipped with multiple radios, power savings and network performance can be maximized by properly routing flows, assigning channels to radios and identifying nodes/radios that can be turned off . Thus, the problem we address is a joint channel assignment and routing problem with additional constraints on the node power consumption, which is NP-complete. In this paper, we propose a heuristic, named minimum power channel assignment and routing algorithm (MP-CARA), which is guaranteed to return a local optimum for this problem. Based on a theoretical analysis that we present in the paper, which gives an upper bound on the outage probability as a function of the constraint on power consumption, we can guarantee that the probability that a node runs out of power with MP-CARA falls below a desired threshold. The performance of MP-CARA is assessed by means of an extensive simulation study aiming to compare the solutions returned by MP-CARA to those found by other heuristics proposed in the literature.

Mobility Prediction Based Joint Stable Routing and Channel Assignment for Mobile Ad Hoc Cognitive Networks

Link instability and channel interference cause significant performance degradation to mobile ad hoc cognitive networks (MACNets). Existing work designs routing and assigns channels separately or does not consider mobility prediction and channel vacation to primary nodes. In this paper, we investigate how to jointly optimize route setup and channel assignment. Firstly, we propose an integrated data transmission cost (IDTC) to quantitatively measure the communication quality of links. This novel routing metric IDTC integratively considers 1) node mobility, 2) co-channel interference among primary and cognitive nodes, 3) relay workload on a specified channel, and 4) distance between the relay and the destination node. We, then, design channel assignment algorithms that completely avoid the interference with primary nodes and minimize the conflict to cognitive nodes. Finally, we propose a joint stable routing and channel assignment (J-SRCA) protocol based on mobility prediction for the network throughput maximization. In our J-SRCA, each link selected hop by hop is simultaneously assigned an interference-avoiding channel during a route setup. NS2-based simulation results demonstrate that our J-SRCA significantly improves various network performance, and the higher interference degree cognitive networks experience, the more improvement our J-SRCA will bring to the networks.

State-Aware Re-configuration Model for Multi-Radio Wireless Mesh Networks

Joint channel assignment and routing is a well-known problem in multi-radio wireless mesh networks for which optimal configurations is required to optimize the overall throughput and fairness. However, other objectives need to be considered in order to provide a high quality service to network users when it deployed with high traffic dynamic. In this paper, we propose a re-configuration optimization model that optimizes the network throughput in addition to reducing the disruption to the mesh clients’ traffic due to the re-configuration process. In this multi-objective optimization model, four objective functions are proposed to be minimized namely maximum link-channel utilization, network average contention, channel re-assignment cost, and re-routing cost. The latter two objectives focus on reducing the re-configuration overhead. This is to reduce the amount of disrupted traffic due to the channel switching and path re-routing resulted from applying the new configuration. In order to adapt to traffic dynamics in the network which might be caused by many factors i.e. users’ mobility, a centralized heuristic re-configuration algorithm called State-Aware Joint Routing and Channel Assignment (SA-JRCA) is proposed in this research based on our re-configuration model. The proposed algorithm re-assigns channels to radios and re-configures flows’ routes with aim of achieving a tradeoff between maximizing the network throughput and minimizing the re-configuration overhead. The ns-2 simulator is used as simulation tool and various metrics are evaluated. These metrics include channel-link utilization, channel re-assignment cost, re-routing cost, throughput, and delay. Simulation results show the good performance of SA-JRCA in term of packet delivery ratio, aggregated throughput and re-configuration overhead. It also shows higher stability to the traffic variation in comparison with other compared algorithms which suffer from performance degradation when high traffic dynamics is applied.

Joint Channel Assignment and Routing in Multiradio Multichannel Wireless Mesh Networks: Design Considerations and Approaches

Multiradio wireless mesh network is a promising architecture that improves the network capacity by exploiting multiple radio channels concurrently. Channel assignment and routing are underlying challenges in multiradio architectures since both determine the traffic distribution over links and channels. The interdependency between channel assignments and routing promotes toward the joint solutions for efficient configurations. This paper presents an in-depth review of the joint approaches of channel assignment and routing in multiradio wireless mesh networks. First, the key design issues, modeling, and approaches are identified and discussed. Second, existing algorithms for joint channel assignment and routing are presented and classified based on the channel assignment types. Furthermore, the set of reconfiguration algorithms to adapt the network traffic dynamics is also discussed. Finally, the paper presents some multiradio practical implementations and test-beds and points out the future research directions.

Route selection for interference minimization to primary users in cognitive radio ad hoc networks: A cross layer approach

An opportunistic routing problem in a cognitive radio ad hoc network is investigated with an aim to minimize the interference to primary users (PUs) and under the constraint of a minimum end-to-end data rate for secondary users (SUs). Both amplify-and-forward (AF) and decode-and-forward (DF) relaying techniques are considered for message forwarding by SU nodes in the network. Unlike popular transmit power control based solutions for interference management in cognitive radio networks, we adopt a cross layer approach. The optimization problem is formulated as a joint power control, channel assignment and route selection problem. Next, closed form expression for transmission power is derived and corresponding channel selection scheme and routing metric are designed based on this solution. The proposed route selection schemes are shown to depend not only on gains of the interference channels between SUs and PUs but also on the values of the spectrum sensing parameters at the SU nodes in the network. Two distributed routing schemes are proposed based on our analysis; (i) optimal_DF and (ii) suboptimal_AF. The routing schemes could be implemented using existing table driven as well as on demand routing protocols. Extensive simulation results are provided to evaluate performance of our proposed schemes in random multihop networks. Results show significant reduction in PUs’ average interference experience and impressive performance as opportunistic routing schemes can be achieved by our schemes compared to traditional shortest path based routing schemes. Performance improvement is also reported over prominent recent schemes.

Wave: a distributed scheduling algorithm for convergecast in IEEE 802.15.4e TSCH networks

AbstractThe IEEE 802.15.4e MAC amendment has been proposed to meet the requirements of industrial applications. Using slotted medium access with channel hopping, the MAC layer orchestrates the medium accesses of nodes according to a given schedule. Nevertheless, this amendment does not specify how this schedule is computed. The purpose of this paper is to propose a distributed joint time slot and channel assignment, called Wave, for data gathering in low‐power lossy networks. This schedule targets minimised data convergecast delays by reducing the total number of slots in the schedule. Moreover, Wave ensures the absence of conflicting transmissions in the schedule provided. In such a schedule, a node is awake only during its transmission slots and those of its children in the convergecast routing graph. Thus, energy efficiency is ensured. In this paper, we present Wave with its properties (e.g. support of heterogeneous traffic, support of a sink equipped with multiple interfaces, worst case delays and buffer size) and compare it with a centralised scheduling algorithm like TMCP and a distributed one like DeTAS. Simulation results show the good performance of Wave compared with TMCP. Because in an industrial environment, several routing graphs can coexist, we study how Wave supports this coexistence. Copyright © 2015 John Wiley & Sons, Ltd.

Joint channel and sink assignment for data collection in cognitive wireless sensor networks

SummaryData collection is a fundamental operation in cognitive wireless sensor networks (CWSNs). However, previous works on data collection assume that a node can transmit data to any node within its transmission range, which is not reasonable in CWSNs. To ensure that the previous works can be applied in CWSNs, this paper focuses on the joint channel and sink assignment problem, which is a critical preparatory work for data collection in CWSNs. Because the capacity performance of a CWSN is usually considered as a key problem in fundamental understanding, we are interested in finding a joint channel and sink assignment for each sensor node, such that the minimum capacity of all sensor nodes is maximized. We formulate our problem as a mixed integer linear program by some elaborate mathematical skills. Then, two algorithms based on greedy strategy and linear relaxation technique are proposed. Extensive simulations results show that our algorithms are efficient and able to achieve near‐optimal performance. Copyright © 2015 John Wiley & Sons, Ltd.

Optimized interference aware joint channel assignment model for wireless mesh network

In this paper, linear optimization is used to model the interference aware joint channel assignment problem in Wireless Mesh Networks. The model selects the channels for the interfering links such that interference is minimized, overall throughput of the network is maximized, and network capacity is fairly distributed among the interfering links. The interference is minimized by classifying the interfering links into four different classes depending upon the geometric location of the sender and receiver of a link (i.e., Sender Connected, Asymmetric Incomplete State, Symmetric Incomplete State, and Far Hidden interfering links). Further, the classes of interfering links are assigned with distinct channels through optimized spectral re-usability of joint channels available in 2.4 GHz ISM band. As a result, it increases the simultaneous transmissions among the interfering links which in turn increases the aggregate throughput of the network while ensuring that capacity is fairly distributed among the interfering links. Numerical results indicated that joint channel assignment model has achieved better performance than non-overlapping channel assignment models. Hence, this validates the model, which can serve as a benchmark in the design and deployment of wireless mesh networks.

Combined channel assignment and network coded opportunistic routing in cognitive radio networks

In this paper, we investigate the joint opportunistic routing and channel assignment problem in multi-channel multi-radio (MCMR) cognitive radio networks (CRNs) for improving the aggregate throughput of the secondary users. We first present the nonlinear programming optimization model for this joint problem, taking into account the feature of CRNs-channel uncertainty. In order to reduce the computational complexity of the problem, we present a heuristic algorithm to select forwarding candidates and assign channels in CRNs, including candidate selection algorithm considering the queue state of a node and expected transmission count (ETX), and channel assignment algorithm taking into account the transmission time and the available time of a given channel. Our simulation results show that the proposed scheme Channel Assignment and Network Coded Opportunistic Routing, (CANCOR) performs better than the traditional routing and classical opportunistic routing in which channel assignment strategy is employed.

Distributed joint flow-radio and channel assignment using partially overlapping channels in multi-radio wireless mesh networks

Equipping mesh nodes with multiple radios that support multiple wireless channels is considered a promising solution to overcome the capacity limitation of single-radio wireless mesh networks. However, careful and intelligent radio resource management is needed to take full advantage of the extra radios on the mesh nodes. Flow-radio assignment and channel assignment procedures should obey the physical constraints imposed by the radios as well as the topological constraints imposed by routing. Varying numbers of wireless channels are available for the channel assignment procedure for different wireless communication standards. To further complicate the problem, the wireless communication standard implemented by the radios of the wireless mesh network may define overlapping as well as orthogonal channels, as in the case of the IEEE 802.11b/g family of standards. This paper presents Distributed Flow-Radio Channel Assignment, a distributed joint flow-radio and channel assignment scheme and the accompanying distributed protocol in the context of multi-channel multi-radio wireless mesh networks. The scheme’s performance is evaluated on small networks for which the optimal flow-radio and channel configuration can be computed, as well as on large random topologies.

JRCAP: A Joint Routing and Channel Assignment Protocol for Multi-radio Multi-channel IEEE 802.11s Mesh Networks

For minimizing contention and interference among co-channel devices, efficient channel selection is essential in 802.11 mesh deployments. The IEEE 802.11 standard provides at least three non overlapping channels. Thus, a node equipped with more than one Network Interface Card can operate on different channels simultaneously. This may increase the aggregate bandwidth available for end users and thereby support a plurality of QoS-sensitive applications. In this work, we propose a joint routing and channel assignment protocol (JRCAP) that defines a density based clustering algorithm for channel allocation (DCCA). DCCA partitions the mesh network into balanced clusters and affects a fixed and static channel to each cluster. Moreover, the JRCAP uses a routing protocol that combines routing and channel allocation for establishing routes and selecting channels for links forming the path. It also uses a new routing metric maximum residual capacity that considers channel diversity, data rate and channel load. We evaluate the performance of the JRCAP through simulation and we compare it to the distributed Hyacinth. Obtained results show that our solution achieves better performance than Hyacinth.