Distributed Link Scheduling Research Articles

A Reassessment on Applying Protocol Interference Model Under Rayleigh Fading: From Perspective of Link Scheduling

Link scheduling plays a pivotal role in accommodating stringent reliability and latency requirements. In this paper, we focus on the availability and effectiveness of applying protocol interference model (PIM) under Rayleigh fading model to solve the problem. The motivation is that PIM caters to distributed link scheduling algorithm design, but usually lead to irrationality due to its localization behavior. While Rayleigh fading model can accurately describe the inherent characteristic of wireless signal propagation, but the features of global interference and channel fading make algorithm design more challenging. To be specific, we first remove the effect of channel fading on algorithmic design by establishing the relationship between Rayleigh fading model and non-fading model. We then propose a centralized once link elimination (OLE) algorithm by utilizing local nature of PIM, and achieve its distributed implementation based on the message delivery with time complexity of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(\Delta_{\max}\ln\Delta_{\max})$</tex-math> </inline-formula> , where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta_{\max}$</tex-math> </inline-formula> is the maximum number of nodes around a given node inside some range. Furthermore, based on random contention resolution, we design another distributed algorithm to schedule all the links within <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(\Delta^{3}_{\max}\ln\Delta_{\max})$</tex-math> </inline-formula> rounds. Simulations show that the PIM is of great confidence as same as Rayleigh fading model, and the proposed algorithms outperform three popular link scheduling algorithms.

Traffic rate agnostic end-to-end delay optimization using receiver-based adaptive link scheduling in 6TiSCH networks

Link scheduling is a key component in 6TiSCH networks. It mainly specifies a node is allowed to transmit packets through which link at what time and in which channel. There exist many link scheduling schemes in the literature for 6TiSCH networks. Among the distributed schemes, the Self-healing distributed scheduling for end-to-end delay optimization (Stratum) was specifically devised to minimize end-to-end latency. However, it performs worse in case of higher traffic rates. On the other hand, the de-facto link scheduling standard Minimal Scheduling Function (MSF) allocates cells (i.e. timeslot and channel) randomly in a slotframe for scheduling transmissions, and thus its end-to-end delay performance is not good under all traffic rates. Therefore, this paper proposes a traffic rate agnostic distributed link scheduling function (RTDS) for 6TiSCH networks. The RTDS follows a receiver-based cell selection and allocation strategy to reduce the waiting time of a packet in the buffer of receiving node before forwarding the packet towards final destination. Unlike MSF, the RTDS uses lesser number of control packet exchanges to adapt the schedule of a link based on the present network condition and traffic rate. The proposed RTDS scheme minimizes end-to-end latency under any traffic rate. RTDS is implemented in the 6TiSCH simulator. Simulation results show that RTDS can significantly improve the end-to-end latency compared to the benchmark schemes. For example, in an 80-node network, the RTDS reduces end-to-end latency by 58% and 43% in low and high traffic rates, respectively, compared to that in MSF. Further, it outperforms Stratum by 77% and 75% under the low and high traffic rates, respectively.

Multi-agent reinforcement learning enabled link scheduling for next generation Internet of Things

In next generation Internet of Things (NG-IoT) networks, numerous pieces of information are aggregated from the user devices and sensor nodes to the local computing units for further computing to support high-level applications. Those multitudinous transmission demands have raised new challenges for current link scheduling protocols. The centralized link scheduling protocols are inappropriate in some large-scale NG-IoT scenarios. The previously distributed link scheduling uses the randomized transmission scheme to avoid interference, making it hard to utilize the bandwidth resources fully. The multi-agent machine learning (MAML) technique is a potential approach to finding the most optimal link scheduling strategy. At the same time, the over-large state space will take a long time for them to approach the optimal solution, which reduces the practicality of the MAML. To fully utilize the bandwidth resource and improve the efficiency of link scheduling, this paper studies a multi-agent reinforcement learning enabled link scheduling problem. Different from the conventional MAML techniques that randomly select a state to do their exploration, in our multi-agent reinforcement learning algorithm, a good state is firstly obtained within polynomial time steps by executing a distributed and randomized sub-algorithm. We say a state is good if it is not far from the optimal state. Then, our multi-agent reinforcement learning scheme starts from the good state and does its exploration with an ɛ greedy scheme, which significantly reduces the time steps to get close to the optimal link scheduling strategy. Extensive simulations are conducted to investigate the performance of our work.

Joint Distributed Link Scheduling and Power Allocation for Content Delivery in Wireless Caching Networks

In wireless caching networks, the design of the content delivery method must consider random user requests, caching states, network topology, and interference management. In this article, we establish a general framework for content delivery in wireless caching networks without stringent assumptions that restrict the network structure and interference model. Based on the framework, we propose a dynamic and distributed link scheduling and power allocation scheme for content delivery that is assisted by belief-propagation (BP) algorithms. The proposed scheme achieves three critical purposes of wireless caching networks: 1) limiting the delay of user request satisfactions, 2) maintaining the power efficiency of caching nodes, and 3) managing interference among users. In addition, we address the intrinsic problem of the BP algorithm in our network model, proposing a matching algorithm for one-to-one link scheduling. Simulation results show that the proposed scheme provides almost the same delay performance as the optimal scheme found through an exhaustive search at the expense of a little additional power consumption and does not require a clustering method and orthogonal resources in a large-scale D2D network.

Distributed link scheduling in wireless networks

This work investigates distributed transmission scheduling in wireless networks. Due to interference constraints, “neighboring links” cannot be simultaneously activated, otherwise transmissions will fail. Here, we consider any binary model of interference. We use the model described by Bui et al. in [L. X. Bui, S. Sanghavi and R. Srikant, Distributed link scheduling with constant overhead, IEEE/ACM Trans. Netw. 17(5) (2009) 1467–1480; S. Sanghavi, L. Bui and R. Srikant, Distributed link scheduling with constant overhead, in Proc. ACM Sigmetrics (San Diego, CA, USA, 2007), pp. 313–324.]. We assume that time is slotted and during each slot there are two phases: one control phase in which a link scheduling algorithm determines a set of non-interfering links to be activated, and a data phase in which data is sent through these links. We assume random arrivals on each link during each slot, so that a queue is associated to each link. Since nodes do not have a global knowledge of the queues sizes, our aim (like in [L. X. Bui, S. Sanghavi and R. Srikant, Distributed link scheduling with constant overhead, IEEE/ACM Trans. Netw. 17(5) (2009) 1467–1480; S. Sanghavi, L. Bui and R. Srikant, Distributed link scheduling with constant overhead, in Proc. ACM Sigmetrics (San Diego, CA, USA, 2007), pp. 313–324.]) is to design a distributed link scheduling algorithm. To be efficient, the control phase should be as short as possible; this is done by exchanging control messages during a constant number of mini-slots (constant overhead). In this paper, we design the first fully distributed local algorithm with the following properties: it works for any arbitrary binary interference model; it has a constant overhead (independent of the size of the network and the values of the queues), and it does not require any knowledge of the queue-lengths. We prove that this algorithm gives a maximal set of active links, where for any non-active link there exists at least one active link in its interference set. We also establish sufficient conditions for stability under general Markovian assumptions. Finally, the performance of our algorithm (throughput, stability) is investigated and compared via simulations to that of previously proposed schemes.

A Novel Medium Access Control Algorithm for Ad Hoc Networks Based on Ising Model

Medium Access Control (MAC) scheduling in ad hoc networks is a challenging task due to the trade-offs between fairness, delay and throughput. In this work, we propose a distributed link scheduling algorithm based on the Ising Model from statistical mechanics, by associating a novel Hamiltonian measure with the network such that its optimization yields a feasible schedule. This work overcomes the shortcomings of previous Ising Model based algorithms by incorporating queuing and servicing dynamics as well as fairness measures for improving aggregate throughput and network latency. Our simulations show considerable improvement in performance compared to existing benchmarks over a variety of traffic arrival patterns and network topologies.

Distributed Link Scheduling Algorithm Based on Successive Interference Cancellation in MIMO Wireless Networks

The performance of multiple input multiple output (MIMO) wireless networks is limited mainly by concurrent interference among sensor nodes. Effective link scheduling algorithms with the technology of successive interference cancellation (SIC) can maximize throughput in MIMO wireless networks. Most previous works on link scheduling in MIMO wireless networks did not consider SIC. In this paper, we propose a MIMO-SIC (MSIC) algorithm under the SINR model. First, a mathematical framework is established for the cross-layer optimization of routing and scheduling, with constraints of traffic balance and link capacity. Second, the interference regions are divided to characterize the level of interference between links. Finally, we propose a distributed link scheduling algorithm based on MSIC to eliminate the interference between competing links in the MIMO network. Experimental results show that the MSIC algorithm can increase the end-to-end throughput per unit by approximately 73% on average compared with non-SIC algorithms.

Cross-Layer MAC Protocol for Unbiased Average Consensus Under Random Interference

Wireless Sensor Networks have been revealed as a powerful technology to solve many different problems through sensor nodes cooperation. One important cooperative process is the so-called average gossip algorithm, which constitutes a building block to perform many inference tasks in an efficient and distributed manner. From the theoretical designs proposed in most previous work, this algorithm requires instantaneous symmetric links in order to reach average consensus. However, in a realistic scenario wireless communications are subject to interferences and other environmental factors, which results in random instantaneous topologies that are, in general, asymmetric. Consequently, the estimation of the average obtained by the gossip algorithm is a random variable, which its realizations may significantly differ from the average value. In the present paper, we first derive a sufficient conditions for any MAC protocol to guarantee that the expected value of the obtained consensus random variable is the average of the initial values (unbiased estimator), while the variance of the estimator is minimum. Then, we propose a cross-layer and distributed link scheduling protocol based on carrier sense, which besides avoiding collisions, ensures both an unbiased estimation and close to minimum variance values. Extensive numerical results are presented to show the validity and efficiency of the proposed approach.

Localized and distributed link scheduling algorithms in IoT under rayleigh fading

The Internet of Things (IoT) is rapidly gaining ground in future wireless communications. Transmission reliability and latency are two significant measurements for the utilization of the IoT. In this paper, we aim to improve reliability and latency requirements by solving the link scheduling problem. Under the Rayleigh fading model, a more realistic interference model, we first localize the global interference by ignoring the interference outside some certain distance, and obtain the success probability of a transmission at least 1−ϵ, where ϵ is an acceptable error probability of a transmission. Based on this key result, we then design two localized and distributed algorithms for one-slot scheduling problem (i.e., how to ensure that the selected links have high transmission reliability or can be scheduled successfully). In addition, we design a localized and distributed algorithm with time complexity of O(Δmax′T,rlogn) to resolve latency minimization problem (i.e., minimize the number of time slots until all transmissions were successful), where Δmax′T,r is the maximum number of senders within RT centered at a receiver in the network, where RT is transmission range of a node. Theoretical analysis and extensive simulations demonstrate that the proposed algorithms can improve the reliability and latency requirements significantly.

Efficient CSMA Using Regional Free Energy Approximations

Distributed link scheduling algorithms based on carrier sense multiple access and Gibbs sampling are known to achieve throughput optimality, if certain parameters called the fugacities are appropriately chosen. However, the problem of computing these fugacities is NP-hard. Further, the complexity of the existing stochastic gradient descent-based algorithms that compute the exact fugacities scales exponentially with the network size. In this paper, we propose a general framework to estimate the fugacities using regional free energy approximations . In particular, we derive explicit expressions for approximate fugacities corresponding to any feasible service rate vector. We further prove that our approximate fugacities are exact for the class of chordal graphs. A distinguishing feature of our work is that the regional approximations that we propose are tailored to conflict graphs with small cycles, which is a typical characteristic of wireless networks. Numerical results indicate that the proposed methods are quite accurate, and significantly outperform the existing approximation techniques.

SINBADLinQ: SINR based distributed link scheduling for device‐to‐device networks

A new autonomous distributed link scheduling scheme, SINBADLinQ, for device-to-device networks is proposed. SINBADLinQ operates with a modified signal-to-inference-plus-noise ratio. The new link scheduling scheme outperforms recently proposed ITLinQ and ITLinQ+ with or without global scheduling information sharing.

QC2LinQ: QoS and Channel-Aware Distributed Link Scheduler for D2D Communication

We study a distributed link scheduling problem for device-to-device (D2D) communication considering the quality-of-service (QoS) requirements and time-varying channel conditions of D2D links. To this end, we first study an optimal centralized link scheduling problem maximizing the total average sum-rate while satisfying the QoS requirements of D2D links. We then abstract the important scheduling principles of the optimal link scheduling, i.e., giving more chance to be scheduled to the links which have a good channel condition and do not satisfy the QoS requirement, in order to utilize them to develop distributed link scheduling algorithms. With the scheduling principles, we develop a procedure with which D2D links can share their degree of QoS unsatisfaction and channel condition with each other and generate their scheduling priorities according to the shared information in a distributed manner. We also develop a novel distributed link scheduling criterion with which D2D links determine their link scheduling. By using them, we propose distributed link scheduling algorithms, QCLinQ and QC $^{2}$ LinQ, which have significantly smaller signaling overhead and low computational complexity compared with the centralized optimal link scheduling algorithm. Moreover, they closely meet the QoS requirements of D2D links while achieving significant sum-rate improvement over conventional distributed algorithms.

A Novel Distributed Max-Weight Link Scheduler for Multi-Transmit/Receive Wireless Mesh Networks

Multi-transmit–receive capability is fast becoming a significant feature of next-generation wireless mesh networks. It enables routers to transmit or receive distinct packets from multiple neighbors simultaneously. A key problem, however, is designing a distributed link-scheduling algorithm that ensures high network capacity. In this paper, we propose dMaxQ, which is a novel queue-length-aware distributed link scheduler that requires only one-hop neighbors' queue information and uses the celebrated max-weight policy in a distributed manner. We have evaluated the performance of dMaxQ in different network topologies for both single-hop and multihop traffic models and compared it against other approaches, including two queue-length-aware centralized algorithms and state-of-the-art distributed approaches: JazzyMAC and receive-oriented multiple access. The results show that for single-hop and multihop traffic scenarios, dMaxQ obtains, respectively, 100% and 90% of the throughput achieved by the theoretical centralized policy. Other distributed algorithms, such as JazzyMAC, only managed 25% of the theoretical throughput.

Optimality of Treating Interference as Noise: A Combinatorial Perspective

For single-antenna Gaussian interference channels, we reformulate the problem of determining the generalized degrees of freedom (GDoF) region achievable by treating interference as Gaussian noise (TIN) derived by Geng et al. from a combinatorial optimization perspective. We show that the TIN power control problem can be cast into an assignment problem, such that the globally optimal power allocation variables can be obtained by well-known polynomial time algorithms (e.g., centralized Hungarian method or distributed Auction algorithm). Furthermore, the expression of the TIN-achievable GDoF region (TINA region) can be substantially simplified with the aid of maximum weighted matchings. We also provide conditions under which the TINA region is a convex polytope that relax those by Geng et al. For these new conditions, together with a channel connectivity (i.e., interference topology) condition, we show TIN optimality for a new class of interference networks that is not included, nor includes, the class found by Geng et al. Building on the above insights, we consider the problem of joint link scheduling and power control in wireless networks, which has been widely studied as a basic physical layer mechanism for device-to-device communications. Inspired by the relaxed TIN channel strength condition as well as the assignment-based power allocation, we propose a low-complexity GDoF-based distributed link scheduling and power control mechanism (ITLinQ+) that improves upon the ITLinQ scheme proposed by Naderializadeh and Avestimehr and further improves over the heuristic approach known as FlashLinQ. It is demonstrated by simulation that ITLinQ+ without power control provides significant average network throughput gains over both ITLinQ and FlashLinQ, and yet still maintains the same level of implementation complexity. Furthermore, when ITLinQ+ is augmented by power control, it provides an energy efficiency substantially larger than that of ITLinQ and FlashLinQ, at the cost of additional complexity and some signaling overhead.

Utility Bounds of Joint Congestion and Medium Access Control for CSMA based Wireless Networks

In this paper, we study the problem of network utility maximization in a CSMA based multi-hop wireless network. Existing work in this aspect typically adopted continuous time Markov model for performance modelling, which fails to consider the channel conflict impact in actual CSMA networks. To maximize the utility of a CSMA based wireless network with channel conflict, in this paper, we first model its weighted network capacity (i.e., network capacity weighted by link queue length) and then propose a distributed link scheduling algorithm, called CSMA based Maximal-Weight Scheduling (C-MWS), to maximize the weighted network capacity. We derive the upper and lower bounds of network utility based on C-MWS. The derived bounds can help us to tune the C-MWS parameters for C-MWS to work in a distributed wireless network. Simulation results show that the joint optimization based on C-MWS can achieve near-optimal network utility when appropriate algorithm parameters are chosen and also show that the derived utility upper bound is very tight.

Link scheduling schemes with on‐off interference map for device‐to‐device communications

New distributed link scheduling schemes based on a recently proposed device-to-device (D2D) communication technology, FlashLinQ are studied. FlashLinQ is an orthogonal frequency division multiplexing-based synchronous D2D communication system, which achieves a high data rate at longer communication ranges over a licensed spectrum. In this method, some links are selected for data traffic for efficient frequency reuse to avoid interference in D2D links. Where every link is assigned a scheduling priority, so in TX (transmitter) and RX (receiver) yielding, the links which are highly interfered by higher priority links give up communication. However, this technique causes inefficiency in the resource reuse from the cascade yielding problem because link scheduling is performed individually by its RX and TX nodes. To deal with this problem, the authors propose two new link scheduling schemes based on a binary matrix called on-off interference map (I-Map), which indicates strong interference between links. In these schemes, each TX generates a binary I-Map matrix with the collective information from TX and RX blocks. With the common I-Map matrix that displays inter-link interference between D2D links, the proposed schemes achieve better performance as compared to the conventional distributed FlashLinQ scheduling scheme.

Adaptive yielding scheme for link scheduling in OFDM-based synchronous device-to-device (D2D) communication system

Compared to asynchronous contention-based random access, e.g., carrier sensing multiple access, synchronous and distributed link scheduling for orthogonal frequency-division multiplexing (OFDM) systems is a viable solution to improve system throughput for device-to-device (D2D) ad hoc network. In particular, spatial spectral efficiency can be improved by scheduling as many concurrent D2D links necessary to satisfy individual signal-to-interference ratio (SIR) requirements. In this paper, we propose an adaptive yielding mechanism that can further improve the spatial spectral efficiency by allowing for more concurrent D2D links whenever more interference can be accepted, e.g., when the instantaneous bandwidth efficiency requirement is less than the current link capacity. Even if the system throughput varies with the link density, it is shown that the average system throughput can be significantly improved by the proposed yielding mechanism.

能量有效的分布式链路调度协议

To decrease the scheduling length and energy cost of a wireless sensor network,a Distributed Link Scheduling(DLS)protocol was proposed based on graph coloring.With proposed scheme mentioned in the protocol,every node was required to construct its two-hop conflict graph,and the scheduling order of every link was decided by its priority and interference degree in the conflict graph. The proposed DLS algorithm relaxes the problem of longer scheduling caused by randomly scheduling and frequent state transition in traditional algorithms.Since the DLS can assign the adjacent slot for every node,the times of node's state transition and the energy cost can be decreased.The efficiency on decreasing the scheduling length and network energy cost of DLS was analyzed.The simulation results show that the scheduling length of the proposed DLS protocol is less about 1-2slots than thoseof the Distributed Scheduling-fixed Power Protocol Interference Model(DS-fPrIM)and Distributed RANDomized time slot scheduling(DRAND)and its scheduling energy cost is the same as that of the DS-fPrIM,but less than that of the DRAND.Moreover,the state transition of the DLS is once less than those of the DS-fPrIM and DRAND.The results also indicate that the proposed DLS protocol has good performance on energy efficiency.

Link Scheduling for Exploiting Spatial Reuse in Multihop MIMO Networks

Multiple-Input-Multiple-Output (MIMO) has great potential for enhancing the throughput of multihop wireless networks via spatial multiplexing or spatial reuse. Spatial reuse with Stream Control (SC) provides a considerable improvement of the network throughput over spatial multiplexing. The gain of spatial reuse, however, is still not fully exploited. There exist large numbers of additional data streams, which could be transmitted concurrently with those data streams scheduled by stream control at certain time slots and vicinities. In this paper, we address the issue of MIMO link scheduling to maximize the gain of spatial reuse and thus network throughput. We propose a Receiver-Oriented Interference Suppression model (ROIS), based on which we design both centralized and distributed link scheduling algorithms to fully exploit the gain of spatial reuse in multihop MIMO networks. Further, we address the traffic-aware link scheduling problem by injecting nonuniform traffic load into the network. Through theoretical analysis and comprehensive performance evaluation, we achieve the following results: 1) link scheduling based on ROIS achieves significant higher network throughput than that based on stream control, with any interference range, number of antennas, and average hop length of data flows. 2) The traffic-aware scheduling is enticingly complementary to the link scheduling based on ROIS model. Accordingly, the two scheduling schemes can be combined to further enhance the network throughput.

Distributed link scheduling with constant overhead

This paper proposes a new class of simple, distributed algorithms for scheduling in wireless networks. The algorithms generate new schedules in a distributed manner via simple local changes to existing schedules. The class is parameterized by integers k \geq 1. We show that algorithm k of our class achieves k /( k +2) of the capacity region, for every k \geq 1. . The algorithms have small and constant worst-case overheads: in particular, algorithm k generates a new schedule using (a) time less than 4 k +2 round-trip times between neighboring nodes in the network, and (b) at most three control transmissions by any given node, for any k . The control signals are explicitly specified, and face the same interference effects as normal data transmissions. Our class of distributed wireless scheduling algorithms are the first ones guaranteed to achieve any fixed fraction of the capacity region while using small and constant overheads that do not scale with network size. The parameter k explicitly captures the tradeoff between control overhead and scheduler throughput performance and provides a tuning knob protocol designers can use to harness this trade-off in practice.