Throughput Optimal Decentralized Scheduling of Multihop Networks With End-to-End Deadline Constraints: Unreliable Links

Abstract

Consider a multihop wireless network serving multiple flows in which wireless link interference constraints are described by a link interference graph. For such a network, we design routing-scheduling policies that maximize the end-to-end timely throughput of the network. Timely throughput of a flow f is defined as the average rate at which packets of flow f reach their destination node d f within their deadline.Our policy has several surprising characteristics. Firstly, we show that the optimal routing-scheduling decision for an individual packet that is present at a wireless node i ∈ V is solely a function of its location, and "age". Thus, a wireless node i does not require the knowledge of the "global" network state in order to maximize the timely throughput. We notice that in comparison, under the backpressure routing policy, a node i requires only the knowledge of its neighbours queue lengths in order to guarantee maximal stability, and hence is decentralized. The key difference arises due to the fact that in our set-up the packets loose their utility once their "age" has crossed their deadline, thus making the task of optimizing timely throughput much more challenging than that of ensuring network stability. Of course, due to this key difference, the decision process involved in maximizing the timely throughput is also much more complex than that involved in ensuring network-wide queue stabilization. In view of this, our results are somewhat surprising.Secondly, the complexity of algorithms that obtaining the policy scales linearly with the number of links present in the network. In case the network parameters are unknown, we derive iterative "online learning" algorithms that yield the optimal policy.We divide the available bandwidth into multiple sub-channels, and allow a policy to activate a set of non-interfering links on each of the subchannels. We consider several types of constraints on the bandwidth availability. When the wireless network is constrained by the average bandwidth utilization, then the obtained policy is shown to be optimal.In case the wireless network has to operate under a hard constraint on the available bandwidth, we truncate the policy obtained for the network with average bandwidth constraints in order that the bandwidth utilized by it is ≤ K units in each time-slot. We show that this truncated policy is asymptotically optimal as the network traffic is scaled to ∞.

Minimizing Age of Information With Power Constraints: Multi-User Opportunistic Scheduling in Multi-State Time-Varying Channels

“…Cross-layer control strategy to minimize communication latency under transmit power constraints have been studied in [27]- [34]. In [32], a Lazy scheduling policy that assigns scheduling decision based on the queue backlog is proposed.…”

“…• Inspired by [28], [34], [35], in Section IV-(A), we first relax the hard bandwidth constraint (5b) and adopt a sensor level decomposition by using Lagrange multiplier. After relaxation, multiple sensors can be scheduled simultaneously.…”

Optimal Information Updating based on Value of Information

“…In applications where the end-to-end packet delays are required to be small, the notion of "timely throughput", i.e., the throughput of packets that reach their destination before their deadlines, is useful. The works [13], [14] develop decentralized policies that maximize the timely throughput. Another useful metric is that of variance/variations in the packet interdelivery times.…”

Scheduling to Minimize Age of Information in Multi-State Time-Varying Networks with Power Constraints

“…The overall objective is to minimize the expected average AoI performance when network is restricted to bandwidth constraint and scheduling decisions have to satisfy the power constraint of each user. Inspired by [25], we first relax the hard bandwidth constraint and decouple the multi-user scheduling problem into a single user constrained Markov decision process (CMDP). Then we propose a truncated scheduling policy that can achieve an asymptotic average AoI performance over the entire network.…”

“…• A dual-method is proposed to search for the Lagrange multiplier such that the relaxed bandwidth constraint can be satisfied. Inspired by [25], we propose an asymptotic optimal truncated scheduling policy to minimize AoI performance under hard bandwidth constraint. The performance of the algorithm is analyzed and verified through simulations.…”