Distributed Channel Allocation Algorithm Research Articles

A game-theoretic learning approach to QoE-driven resource allocation scheme in 5G-enabled IoT

To significantly promote Internet of Things (IoT) development, 5G network is enabled for supporting IoT communications without the limitation of distance and location. This paper investigates the channel allocation problem for IoT uplink communications in the 5G network, with the aim of improving the quality of experience (QoE) of smart objects (SOs). To begin with, we define a mean opinion score (MOS) function of transmission delay to measure QoE of each SO. For the sum-MOS maximization problem, we leverage a game-theoretic learning approach to solve it. Specifically, the original optimization problem is equivalently transformed into a tractable form. Then, we formulate the converted problem as a game-theoretical framework and define a potential function which has a near-optimum as the optimization objective. To optimize the potential function, a distributed channel allocation algorithm is proposed to converge to the best Nash equilibrium solution which is the global optimum of maximizing the potential function. Finally, numerical results verify the effectiveness of the proposed scheme.

Distributed Resource Allocation for D2D-Assisted Small Cell Networks With Heterogeneous Spectrum

Device-to-device (D2D) communication with increased spectral efficiency and reduced communication delay has undoubtedly become a general trend in future wireless networks. However, when D2D communication is incorporated into small cell networks (SCNs) with large number of randomly overlapped small cells, the co-channel interference between small cell users (SUEs) and D2D users is an inevitable challenge, especially with the heterogeneous spectrum, i.e., licensed spectrum bands and unlicensed spectrum bands. In this paper, we study the downlink channel allocation in D2D-assisted small cell networks with heterogeneous spectrum bands. By taking the required data rate of users and the interference constraint of SUEs into account, we formulate a channel allocation problem integrating channel selection and channel sharing to maximize the network utility, which is the service satisfaction of all users. To derive the solution, we decompose the optimization problem into two games: a potential game and a coalition game. Then, a potential game-based scheme using an interference graph and a coalition scheme with D2D user transferring is proposed to solve these two games, respectively. Based on these schemes, a two-stage distributed channel allocation algorithm is proposed and can converge with low computational complexity. Moreover, the simulation results reveal that the proposed algorithm could achieve high system throughput and network utility.

A Simple Distributed Channel Allocation Algorithm for D2D Communication Pairs

Device-to-device (D2D) communication is a promising technology to achieve high spectrum efficiency, low energy consumption, and enhanced system capacity. In D2D communications, the channel allocation plays a crucial role to avoid interference, which usually involves a centralized coordination. With the increasing number of devices or terminals as well as the dynamic network environment, the computation and information exchange during the centralized channel allocation would be a big burden for wireless networks. We tackle this problem by proposing a distributed channel allocation method with blind rendezvous to enable collision-free concurrent transmissions over multiple channels. Specifically, we first present a receiver-oriented channel allocation algorithm to reduce interference and then propose a sender-jump blind channel rendezvous algorithm based on channel hopping techniques. The proposed channel allocation method allows each sender–receiver pair to obtain an appropriate channel for collision-free transmissions requires no centralized coordination. Theoretical analysis, simulation results and test-bed experiments validate the proposed solution. Our findings reported in this paper may help network designers to contribute in the development of high-density Internet of Things.

Distributed Channel Allocation and Time Slot Optimization for Green Internet of Things.

In sustainable smart cities, power saving is a severe challenge in the energy-constrained Internet of Things (IoT). Efficient utilization of limited multiple non-overlap channels and time resources is a promising solution to reduce the network interference and save energy consumption. In this paper, we propose a joint channel allocation and time slot optimization solution for IoT. First, we propose a channel ranking algorithm which enables each node to rank its available channels based on the channel properties. Then, we propose a distributed channel allocation algorithm so that each node can choose a proper channel based on the channel ranking and its own residual energy. Finally, the sleeping duration and spectrum sensing duration are jointly optimized to maximize the normalized throughput and satisfy energy consumption constraints simultaneously. Different from the former approaches, our proposed solution requires no central coordination or any global information that each node can operate based on its own local information in a total distributed manner. Also, theoretical analysis and extensive simulations have validated that when applying our solution in the network of IoT: (i) each node can be allocated to a proper channel based on the residual energy to balance the lifetime; (ii) the network can rapidly converge to a collision-free transmission through each node’s learning ability in the process of the distributed channel allocation; and (iii) the network throughput is further improved via the dynamic time slot optimization.

Distributed ON/OFF switching and dynamic channel allocation: Decreasing complexity and improving energy efficiency

AbstractHeterogeneous network (HetNet) has emerged as a promising and viable approach to deliver higher‐rate data services. In HetNets, switching OFF base stations (BSs) is known as an effective solution to reduce the energy consumption of networks and thus enables the “greener” networks concept. In this paper, we investigate the impact of the number of energy‐saving modes for BSs on improving energy efficiency. We assume that BSs are able to switch among several modes, ie, different transmission power levels. We apply a no‐regret learning algorithm to choose the BS's operation mode while modeling the BS's operation under dynamic traffic with a Markov process. As a result, we face a trade‐off between energy savings and computational complexity. Furthermore, we use a distributed channel allocation algorithm based on the average cochannel interference power. Simulation results show that energy consumption reduces with increased number of modes. However, increasing the number of modes beyond a certain limit will not have a significant effect on energy efficiency.

Distributed Channel Fast Allocation in Cognitive Wireless Sensor Networks

For the feature of zero delay in continuous relay transmission, wireless sensor networks supporting multiple communication interfaces is much suitable for the data collection and transmission backbone network of coal mine safety monitor and control system which has high demand of reliability in real-time data transmission. Based on in-depth analysis of the existing distributed channel allocation algorithms, this paper proposes an innovative fast distributed channel allocation scheme based on largest edges of network topology (CALENT) with the combination of distributed and architecture features. By comparing with the existing distributed channel allocation Dis-Link algorithm, CALENT has better performance in co-channel interference index and convergence velocity.

Distributed fast channel allocation in cognitive wireless sensor networks

For the feature of zero delay in continuous relay transmission, wireless sensor networks (WSNs) supporting multiple communication interfaces is much suitable for data collection and transmission backbone network of coal mine safety monitor and control system which has high demand of reliability in real-time data transmission. Based on in-depth analysis of the existing distributed channel allocation algorithms, this study proposes an innovative fast distributed channel allocation scheme based on largest edges of network topology (CALENT) with the combination of wireless network architecture features. By comparing with existing distributed channel allocation dis-link algorithm, CALENT has better performance in co-channel interference index and convergence velocity.

Interference Minimization and Dynamic Sub-Carrier Allocation in Broadband Wireless Networks

Efficient channel allocation is the key to fully exploit the signal diversity presented in the multi-carrier physical link in today's broadband wireless access networks. There are mounting evidences that the 4G and future-generation systems will take advantage of two opposite types of access methods, one using centralized control method and the other using a distributed approach. The authors study the distributed channel allocation problem in this article, formulated as a non-linear optimization problem, in broadband wireless networks. The signal properties of the multi-carrier radio interface in 3G and 4G networks are discussed to comprehend the complexity of the channel allocation problem. The authors propose a novel distributed heuristic algorithm based on the particle-swarm searching method. The distributed approach allows user stations to quickly switch sub-carriers with minimum intervention from the base station. The work presented in this paper shows an effective method to allocate a large number of channels while minimizing the possible interference. Extensive numerical experiments are conducted to evaluate several versions of distributed channel allocation algorithm for these new problem settings. The authors' results show that PSO-based method converges quickly in all our numerical experiments despite the high-dimensional searching space. The proposed technologies will eventually allow the true mobile steaming video/audio experience anywhere and anytime, which will have the huge impact to business, entertainment and people's quality of life.

A Distributed Channel Allocation Algorithm for Multi-channel Wireless Networks

A Distributed Channel Allocation Algorithm for Multi-channel Wireless Networks

Performance Comparison of Two Channel Allocation Strategies in Cellular Networks

Channel allocation plays an important role in increasing the throughput and assuring fairness to users not only in traditional cellular networks but also in cognitive radio networks and mesh networks. In this paper, we study the effect of pre-allocating channels to cells with respect to a distributed and fault-tolerant channel allocation algorithm. Results from our extensive performance evaluation indicate that distributed channel allocation algorithms that pre-allocate all channels to cells can have lower call failure rate, call blocking rate, and handoff drop rate compared to algorithms that partially pre-allocate channels or does not pre-allocate channels.

Performance analysis of a threshold based distributed channel allocation algorithm for cellular networks

Rapid advances of the handheld devices and the emergence of the demanding wireless applications require the cellular networks to support the demanding user needs more effectively. The cellular networks are expected to provide these services under a limited bandwidth. Efficient management of the wireless channels by effective channel allocation algorithms is crucial for the performance of any cellular system. To provide a better channel usage performance, dynamic channel allocation schemes have been proposed. Among these schemes, distributed dynamic channel allocation approaches showed good performance results. The two important issues that must be carefully addressed in such algorithms are the efficient co-channel interference avoidance and messaging overhead reduction. In this paper, we focus on our new distributed channel allocation algorithm and evaluate its performance through extensive simulation studies. The performance evaluation results obtained under different traffic load and user mobility conditions, show that the proposed algorithm outperforms other algorithms recently proposed in the literature.

An efficient fault-tolerant distributed channel allocation algorithm for cellular networks

A channel allocation algorithm in a cellular network consists of two parts: a channel acquisition algorithm and a channel selection algorithm. Some of the previous works in this field focused on centralized approaches to allocating channels. But, centralized approaches are neither scalable nor reliable. Recently, distributed dynamic channel allocation algorithms have been proposed, and they have gained a lot of attention due to their high reliability and scalability. But, in most of the algorithms, the cell that wants to borrow a channel has to wait for replies from all its interference neighbors and, hence, is not fault-tolerant. In this paper, we propose a new algorithm that is fault-tolerant and makes full use of the available channels. It can tolerate the failure of mobile nodes as well as static nodes without any significant degradation in service.

D-CAT: An Efficient Algorithm for Distributed Channel Allocation in Cellular Mobile Networks

We propose a distributed channel allocation algorithm based on a threshold scheme, called D-CAT, for cellular mobile networks. The algorithm employs two thresholds: (i) a heavy threshold for determining whether a cell is heavy, or overloaded, and for triggering the channel allocation algorithm; and (ii) a target threshold for indicating the target number of free channels that a heavy cell intends to acquire. Based on the two-threshold scheme, the D-CAT algorithm can determine the optimal number of free channels as well as the cell(s) from where a heavy cell should import channels in order to satisfy the required channel demand. Simulation experiments and analyses show that the proposed algorithm incurs lower overhead for channel allocation and is more efficient in terms of channel utilization than other distributed channel allocation algorithms. It also outperforms other centralized and distributed algorithms in terms of call blocking probability.

Integrating distributed channel allocation and adaptive handoff management for QoS-sensitive cellular networks

Next generation high-speed cellular networks are expected to support multimedia applications, which require QoS provisions. Since frequency spectrum is the most expensive resource in wireless networks, it is a challenge to support QoS using limited frequency spectrum. In the literature, two orthogonal approaches are used to address the bandwidth utilization issue and the QoS provision issue; that is, channel allocation schemes have been proposed to improve bandwidth efficiency, whereas handoff management schemes, based on bandwidth reservation, have been proposed to guarantee a low connection dropping rate. However, little effort has been taken to address both issues together. In this paper, we integrate distributed channel allocation and adaptive handoff management to provide QoS guarantees and efficiently utilize the bandwidth. First, we present a complete distributed distributed channel allocation algorithm and propose techniques to reduce its message complexity and intra-handoff overhead. Second, we integrate the proposed distributed channel allocation algorithm with an adaptive handoff management scheme to provide QoS guarantees and efficiently utilize the bandwidth. Detailed simulation experiments are carried out to evaluate the proposed methodology. Compared to previous schemes, our scheme can significantly reduce the message complexity and intra-handoff overhead. Moreover, the proposed scheme can improve the bandwidth utilization while providing QoS guarantees.

On distributed dynamic channel allocation in mobile cellular networks

Distributed dynamic channel allocation (DDCA) is a fundamental resource management problem in mobile cellular networks. It has a flavor of distributed mutual exclusion but is not exactly a mutual exclusion problem. We establish the exact relationship between the two problems. Specifically, we introduce the problem of relaxed mutual exclusion to model one important aspect of the DDCA problem. We develop a general algorithm that guarantees relaxed mutual exclusion for a single resource and prove necessary and sufficient conditions for the information structure. Considering distributed dynamic channel allocation as a special case of relaxed mutual exclusion, we apply and extend the algorithm to further address the issues that arise in distributed channel allocation such as deadlock resolution, dealing with multiple channels, design of efficient information structures, and channel selection strategies. Based on these results, we propose an example distributed channel allocation scheme using one of the information structures proposed. Analysis and simulation results are provided and show that the results of this research can be used to design more efficient distributed channel allocation algorithms.

Distributed fault-tolerant channel allocation for cellular networks

A channel allocation algorithm includes channel acquisition and channel selection algorithms. Most of the previous work concentrates on the channel selection algorithm since early channel acquisition algorithms are centralized and rely on a mobile switching center (MSC) to accomplish channel acquisition. Distributed channel acquisition algorithms have received considerable attention due to their high reliability and scalability. However, in these algorithms, a borrower needs to consult with its interference neighbors in order to borrow a channel. Thus, the borrower fails to borrow channels when it cannot communicate with any interference neighbor. In real-life networks, under heavy traffic load, a cell has a large probability to experience an intermittent network congestion or even a communication link failure. In existing distributed algorithms, since a cell has to consult with a large number of interference neighbors to borrow a channel, the failure rate will be much higher under heavy traffic load. Therefore, previous distributed channel allocation algorithms are not suitable for real-life networks. We first propose a fault-tolerant channel acquisition algorithm which tolerates communication link failures and node (MH or MSS) failures. Then, we present a channel selection algorithm and integrate it into the distributed acquisition algorithm. Detailed simulation experiments are carried out in order to evaluate our proposed methodology. Simulation results show that our algorithm significantly reduces the failure rate under network congestion, communication link failures, and node failures compared to nonfault-tolerant channel allocation algorithms. Moreover, our algorithm has low message overhead compared to known distributed channel allocation algorithms, and outperforms them in terms of failure rate under uniform as well as nonuniform traffic distribution.

Efficient distributed channel allocation for cellular networks

The performance of a distributed dynamic channel allocation algorithm is measured by the call blocking rate, the number of messages exchanged per channel acquisition and the delay incurred in acquiring a channel. In general, there are two approaches in designing distributed channel allocation algorithms: Search and Update. Both of these approaches have advantages and disadvantages. The update approach has shorter acquisition delay and lower call blocking rate, but higher message complexity. On the other hand, the search approach has lower message complexity, but longer acquisition delay and higher call blocking rate. In this paper, we first propose a novel distributed acquisition algorithm, which has similar message complexity as the search approach and similar acquisition delay as the update approach. Then, we present a channel selection algorithm and integrate it into our distributed acquisition algorithm. By a rigorous analysis in terms of delay and message complexity, we show that our channel selection algorithm performs significantly better than the update approach [X. Dong, T.H. Lai, Proceedings of the International Conference on Distributed Computing systems, 1997] and the search approach [R. Prakash, N. Shivaratri, M. Singhal, Proceedings of the 14th ACM Symposium on Principles of Distributed Computing, 1995, pp. 47–56]. Detailed simulation experiments are carried out in order to evaluate our proposed methodology. The performance of our algorithm is compared with those of the Geometric strategy [A. Baiocchi, F.D. Proscoli, F. Grilli, F. Sestini, IEEE Trans. Veh. Technol. February (1995) 14–23], the Search approach [R. Prakash, N. Shivaratri, M. Singhal, Proceedings of the 14th ACM Symposium on Principles of Distributed Computing, 1995, pp. 47–56] and the Update approach [X. Dong, T.H. Lai, Proceedings of the International Conference on Distributed Computing systems, 1997]. Simulation results show that our algorithm outperforms all other approaches in terms of call blocking probability under uniform as well as non-uniform traffic distributions.

An Adaptive Distributed Channel Allocation Strategy for Mobile Cellular Networks

A channel allocation algorithm includes a channel acquisition algorithm and a channel selection algorithm. Most of the previous work concentrates on the channel selection algorithm since early channel allocation algorithms simply use a centralized channel acquisition algorithm, which depends on a mobile switching center (MSC) to accomplish channel acquisition. Recently, distributed channel acquisition algorithms have received considerable attention due to their high reliability and scalability. There are two approaches to designing distributed channel acquisition algorithms: search and update. The update approach has shorter acquisition delay and lower call blocking rate, but higher message complexity. On the other hand, the search approach has lower message complexity, but longer acquisition delay and higher call blocking rate. In this paper, we propose a novel distributed channel acquisition algorithm, which is a significant improvement over both approaches. Also, we identify two guiding principles in designing channel selection algorithms and propose an algorithm which has low call blocking rate and low intrahandoff overhead. By integrating the channel selection algorithm into our channel acquisition algorithm, we get a complete distributed channel allocation algorithm. By keeping the borrowed channels, the channel allocation algorithm makes use of the temporal locality and adapts to the network traffic; i.e., free channels are transferred to hot cells to achieve load balance. Simulation results show that our channel allocation algorithm significantly outperforms the search approach and the update approach in terms of call blocking rate, message complexity, and acquisition delay.