Optimality of periodwise static priority policies in real-time communications

Hou, I-Hong; Truong, Anh; Chakraborty, Santanu

doi:10.1109/cdc.2011.6160881

Cited by 10 publications

(19 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The problem of scheduling traffic in order to satisfy timely throughput constraints of multiple clients being served by a single-hop wireless network is fairly well-understood by now [10]- [19]. For this single-hop network, simple to implement greedy policies are shown to be optimal.…”

Section: Contributions and Past Workmentioning

confidence: 99%

“…In order to implement sub-gradient descent algorithm, each link needs to iterate on its price µ (t) as follows 5 where Π [·] projects the iterates onto a suitable compact set. Since the dual problem (19) is convex, we have, Lemma 2: The price iterations (20) converge to the price vector µ that solves the dual problem (19). We note that in order to carry out the price iterations we need to compute the quantitiesC π (µ(t)) .…”

Section: Obtaining the Optimal Prices µmentioning

confidence: 99%

“…Theorem 1 (Scheduling under Average Link Bandwidth constraints): Consider the problem of optimal scheduling for packets having end-to-end deadline constraints under link-level average constraintsC π ≤ C av , ∀ ∈ E, i.e., the problem (11)- (12). The optimal policy is given by π = ⊗ f π f (µ ), where µ is the solution to the dual problem (19). It implements the policy π f (µ ) that is the solution to the single packet transportation problem with link prices set to µ , for each packet belonging to flow f .…”

Section: Obtaining the Optimal Prices µmentioning

confidence: 99%

See 2 more Smart Citations

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

Singh

Kumar

2019

IEEE Trans. Automat. Contr.

Self Cite

View full text Add to dashboard Cite

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 ∞.

show abstract

Section: Contributions and Past Workmentioning

confidence: 99%

Section: Obtaining the Optimal Prices µmentioning

confidence: 99%

Section: Obtaining the Optimal Prices µmentioning

confidence: 99%

See 1 more Smart Citation

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

Singh

Kumar

2019

IEEE Trans. Automat. Contr.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Next we simplify the stability condition (22) for two special cases: the perfect-channel case (Sec. IV) and the symmetricstructure case (Sec.…”

Section: Stability Condition Of Our Wncsmentioning

confidence: 99%

On Stability Condition of Wireless Networked Control Systems under Joint Design of Control Policy and Network Scheduling Policy

Deng

Tan

Wong

2018

2018 IEEE Conference on Decision and Control (CDC)

View full text Add to dashboard Cite

In this paper, we study a wireless networked control system (WNCS) with N ≥ 2 sub-systems sharing a common wireless channel. Each sub-system consists of a plant and a controller and the control message must be delivered from the controller to the plant through the shared wireless channel. The wireless channel is unreliable due to interference and fading. As a result, a packet can be successfully delivered in a slot with a certain probability. A network scheduling policy determines how to transmit those control messages generated by such N subsystems and directly influences the transmission delay of control messages. We first consider the case that all sub-systems have the same sampling period. We characterize the stability condition of such a WNCS under the joint design of the control policy and the network scheduling policy by means of 2 N linear inequalities. We further simplify the stability condition into only one linear inequality for two special cases: the perfect-channel case where the wireless channel can successfully deliver a control message with certainty in each slot, and the symmetric-structure case where all sub-systems have identical system parameters. We then consider the case that different sub-systems can have different sampling periods, where we characterize a sufficient condition for stability.

show abstract

“…The region Λ unicast 0 is known to be the base of a polymatroid up to a linear scaling [15]. As a result, the weighted sum throughput maximization problem (1) in the special case of serving unicast flows becomes the following problem…”

Section: A the Unicast Throughput Regionmentioning

confidence: 99%

Scheduling multicast traffic with deadlines in wireless networks

Kim

Modiano

2014

IEEE INFOCOM 2014 - IEEE Conference on Computer Communications

View full text Add to dashboard Cite

Abstract-We consider the problem of transmitting multicast flows with hard deadlines over unreliable wireless channels. Every user in the network subscribes to several multicast flows, and requires a minimum throughput for each subscribed flow to meet the QoS constraints. The network controller schedules the transmissions of multicast traffic based on the instant feedback from the users. We characterize the multicast throughput region by analyzing its boundary points, each of which is the solution to a finite-horizon dynamic programming problem over an exponentially large state space. Using backward induction and interchange arguments, we show that the dynamic programming problems are solved by greedy policies that maximize the immediate weighted sum throughput in every slot. Furthermore, we develop a dynamic throughput-optimal policy that achieves any feasible throughput vector by tracking the running performance perceived by the users.

show abstract

Optimality of periodwise static priority policies in real-time communications

Cited by 10 publications

References 5 publications

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

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

On Stability Condition of Wireless Networked Control Systems under Joint Design of Control Policy and Network Scheduling Policy

Scheduling multicast traffic with deadlines in wireless networks

Contact Info

Product

Resources

About