The hybrid medium access control (MAC) protocol, which was first adopted in the IEEE 802.11ax standard, combines contention-based random access (UORA) and contention-free scheduled access (SA) transmissions over orthogonal resource units (RUs). We present a novel fixed-point analysis of saturation throughput and average access delay of hybrid access that accounts for discrete rate adaptation, packet decoding errors, and scheduling. Using this analysis and Markov decision process (MDP) theory, we design a novel dynamic RU allocation policy (ODRAP) for hybrid access. Our analysis and policy design are the first to capture the dynamic flow of users between UORA and SA, and its dependence on the RU allocation. The existing literature has modeled UORA or SA, but not both, or has assumed a fixed number of SA users. We first develop the analysis when the number of packets reported in the buffer status report (BSR) of a user is a geometric random variable. We then present an iterative approach to handle application-specific general distributions. Our numerical results verify the accuracy of the analysis despite its simplicity. Furthermore, they highlight the impact of the number of allocated RUs on the scheduler. ODRAP optimally trades off the throughput with the access delay compared to several benchmark policies.

We consider a dynamic content fetching, caching and delivery problem wherein the contents get updated at a central server, and local copies of a subset of the contents are cached at an edge cache associated with a base station (BS). Upon being requested, the BS can fetch the requested content from the central server and serve or can serve the locally cached version or can deny service. Fetching a content incurs a fixed fetching cost, serving a cached version incurs an ageing cost proportional to the age-of-version (AoV) of the content, and denying service incurs a fixed missing cost. Furthermore, due to unreliability of the channel between the BS and the users, a content delivery can fail, again resulting in a missing cost. We formulate an optimal content fetching, caching and delivery problem to minimize the average cost subject to the cache capacity constraint. This problem belongs to the class of continuous time restless multi-armed bandit (RMAB) problems with state dependent feasible action sets. We show that the single content problem is indexable, derive its Whittle indices and provide a Whittle index based policy for the original multi-content problem. Finally, we numerically evaluate the performance of the proposed policy and compare it to the existing works. We demonstrate that the proposed policy substantially outperforms the existing ones and, performance-wise, is very close to the optimal policy.

The Deficit Round Robin (DRR) scheduler is widely used in network systems for its simplicity and fairness. However, configuring its integer-valued parameters, known as quanta, to meet stringent delay constraints remains a significant challenge. This paper addresses this issue by demonstrating the convexity of the feasible parameter set for a two-flow DRR system under delay constraints. The analysis is then extended to n-flow systems, uncovering key structural properties that guide parameter selection. Additionally, we propose an optimization method to maximize the number of packets served in a round while satisfying delay constraints. The effectiveness of this approach is validated through numerical simulations, providing a practical framework for enhancing DRR scheduling. These findings offer valuable insights into resource allocation strategies for maintaining Quality of Service (QoS) standards in network slicing environments.

Full-duplex (FD) communication is a promising new technology that enables simultaneous transmission and reception in wireless local area networks (WLANs). The benefits of FD on the medium access control (MAC) layer throughput in IEEE 802.11 WLANs are well-documented. However, cross-layer interactions between the FD MAC protocol and transport layer protocols such as Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) are less explored. We consider a WLAN with uplink and downlink TCP flows as well as UDP flows between stations (STAs) and a server via an FD access point (AP). We study an STA-initiated FD MAC protocol in which the AP can transmit on the downlink while receiving on the uplink. Using a novel FD-specific STA saturation approximation, Markov renewal theory, and fixed-point analysis, we derive novel expressions for the uplink and downlink TCP and UDP saturation throughputs. Our analysis shows that the AP is no longer a bottleneck and may be unsaturated unlike in conventional half-duplex (HD) WLANs. Despite greater contention and cross-link interference between STAs, FD achieves a higher TCP throughput than HD. FD causes a significant degradation in the UDP throughput. In the unsaturated regime, FD achieves a lower average downlink TCP packet delay than HD.

Full-duplex (FD) communication promises to double the throughput of wireless local area networks (WLANs) by allowing simultaneous transmission and reception of data. While the benefits of FD on the medium access control (MAC) layer throughput of IEEE 802.11 WLANs are well-studied, the interaction between the transmission control protocol (TCP) and the FD MAC layer is less explored. We consider TCP file uploads and downloads between stations (STAs) and a server via an FD access point (AP). Using a novel FD-specific saturation approximation, Markov renewal theory, and fixed point analysis, we derive novel expressions for the TCP upload and download saturation throughputs. These expressions differ from those derived in the literature for TCP over half-duplex (HD) WLANs, and bring out how the AP is no longer a bottleneck. Despite greater contention between STAs, cross-link interference between transmitting and receiving STAs, and asymmetric payloads due to the different sizes of TCP data packets and TCP acknowledgments, we find that an FD WLAN achieves a significantly higher TCP throughput than a conventional HD WLAN.

The IEEE 802.1CB standard for Frame Replication and Elimination for Reliability (FRER) emphasises improving reliability by introducing link redundancy. In this paper, two approaches towards the elimination of duplicates are implemented on a programmable pipelined switch. The first approach meets the intermittent stream traffic goal of the standard. A sliding window-based algorithm is used for storing and comparing identification numbers of packets. The second approach handles bulk stream traffic by using a hash table along with the sliding window for a faster lookup, making it more scalable. Hash-collision mitigation with the help of stream identification is also incorporated in the hash table approach. The algorithms are implemented in P4 and Micro-C. Latency versus window size obtained for both the approaches and the end-to-end packet loss reduction yielded by FRER in presence of lossy intermediate links are demonstrated.

We study content caching in a network consisting of a server and a base station with a finite-capacity cache. Contents are dynamic. They stochastically arrive in the system, stay for random times, and their popularities also randomly vary while they are alive. Fetching contents from the server and storing in the base station cache incurs a cost. But not having the requested contents at the base station also incurs a cost that reflects QoS deficiency. We study optimal proactive caching to minimise the time-average content miss and caching costs. We formulate this problem as an average cost Markov decision problem that is a restless multi-armed bandit problem. We argue that the problem is indexable and explicitly derives the Whittle indices. Finally, we demonstrate the efficacy of the Whittle index policy via numerical evaluation.

We propose throughput and cost optimal job scheduling algorithms in cloud computing platforms offering Infrastructure as a Service. We first consider online job migration and propose job scheduling algorithms to minimize job migration and server running costs. We consider algorithms that assume knowledge of job-size on the arrival of jobs. We characterize the optimal cost subject to system stability. We develop a drift-plus-penalty framework based algorithm that can achieve optimal cost arbitrarily closely. Specifically, this algorithm yields a tradeoff between delay and costs. We then relax the job-size knowledge assumption and give an algorithm that uses readily offered service to the jobs. We show that this algorithm gives order-wise identical cost as the job size based algorithm. Later, we consider offline job migration that incurs migration delays. We again present throughput optimal algorithms that minimize server running cost. We illustrate the performance of the proposed algorithms and compare these to the existing algorithms via simulation.

We study service scheduling problems in a slotted system in which agents arrive with service requests according to a Bernoulli process and have to leave within two slots after arrival, service costs are quadratic in service rates, and there is also a waiting cost. We consider fixed waiting costs. We frame the problem as an average cost Markov decision process . While the studied system is a linear system with quadratic costs, it has state dependent control. Moreover, it also possesses a non-standard cost function structure rendering the optimization problem complex. Here, we characterize the optimal policy. We also consider a system in which the agents make scheduling decisions for their respective service requests keeping their own cost in view. We frame this scheduling problem as a stochastic game. Here, we provide Nash equilibrium.

We evolve a methodology and define a metric to evaluate Tactile Cyber-Physical Systems (TCPS). Towards this goal, we use the step response analysis, a well-known control-theoretic method. The adoption includes replacing the human operator (or master) with a controller with known characteristics and analyzing its response to slave side step disturbances. The resulting step response curves demonstrate that the Quality of Control (QoC) metric is sensitive to control loop instabilities and serves as a good indicator of potential factors that contribute to operator-side cybersickness. Through experiments, we demonstrate how QoC accounts for network overheads such as the link latency and jitter and non-networking overheads such as the testbed settings and robot performances in a TCPS. We show that there is a one-to-one correlation between QoC and end-to-end latency, jitter, and packet drops of a TCPS implementation. We show through experiments how QoC can be used to estimate positional errors in tactile-visual control applications. Since higher positional errors can result in poor task performance, estimating them is useful in developing a better-performing TCPS. We also evaluate a TCPS using Fitts’ test and compare its results with QoC. We show that QoC is useful in distinguishing TCPS with differences in their specifications that are not detectable using Fitts’ test.

Cybersickness and control-loop instabilities are two main concerns in Tactile Cyber-Physical Systems (TCPS). TCPS applications demand stringent bounds on end-to-end latencies to avoid their occurrences. Traditional best-effort networks cannot guarantee packet latencies in the presence of external traffic. However, emerging deterministic networks such as IEEE 802.1 Time-Sensitive Networking (TSN) can isolate time-critical flows from external traffic using IEEE 802.1Qbv Time-Aware Shaper (TAS) to guarantee bounded end-to-end packet latencies. In this work, we develop eDDSCH-TSN, a decentralized dynamic scheduling protocol to configure non-overlapping gate slots in TAS-enabled TSN switches to support TCPS flows. eDDSCH-TSN supports plug-and-play operation of compatible TCPS terminals with guaranteed minimal end-to-end packet latencies. Compared to the state-of-the-art, eDDSCH-TSN provides three orders lower end-to-end packet latencies for TCPS flows in mid-size networks with 10 hops between source and destination terminals. Further, we also present PYTSN, an open-source discrete-event TSN simulator that we use for evaluating eDDSCH-TSN. In particular, we use PYTSN to show the isolation of TCPS flows from external traffic and plug-and-play operation of TCPS terminals.

Tactile Internet based Cyber-Physical Systems (TCPS) are highly sensitive to component and communication latencies and packet drops. Building a high performing TCPS, thus, necessitates experimenting with different hardware, algorithms, access technologies, and communication protocols. To facilitate such experiments, we have developed TCPSbed, a modular testbed for TCPS. TCPSbed facilitates the integration of different components, both real and simulated, to realize different TCPS applications and evaluate their latency and control performances. TCPSbed’s latency analyzer tool employs a novel method to isolate latencies of individual TCPS components such as the latencies contributed by actuation, sensing, algorithms, and by the network, all in an online fashion. TCPSbed’s method of analyzing stability is also novel. It involves the use of the step response analysis method, a classic control-theoretic method used for analyzing the stability of generic control systems. TCPSbed’s support for edge intelligence modules enables prediction of command and feedback signals at the network’s edge allowing TCPS applications to perform well in adverse network conditions. TCPSbed’s source-code, made available through our GitHub pageTactileInternet, allows developers to extend its features and functionalities further. In this paper, we describe the architecture and implementation details of TCPSbed and demonstrate its features through several proof-of-concept experiments.

We study content caching in a cellular network consisting of a base station with a cache. New contents arrive in the network according to a Poisson process and the contents stay for exponentially distributed times. At any given time, all the contents in the network have the same popularity or request rate. Also, contents’ request rates are time-varying, instantaneous request rates being a decreasing function of the number of contents in the network. Precaching contents at the base station incurs a cost. However, fetching contents from the server on being requested incurs an even higher cost. We formulate caching problem as a Markov decision process and derive the optimal caching policy. We also propose a Reinforcement Learning based algorithm that yields precaching decisions when system parameters are unknown. Numerical results show that the proposed algorithm’s time averaged cost is close to the optimal average cost.

We study service scheduling problems in a slotted system in which jobs arrive according to a Bernoulli process and have to leave within two slots after arrival, service costs are quadratic in service rates, and there is also a linear waiting cost. We illustrate how these systems can be used to model CPU speed scaling, EV charging at a charging center, load scheduling in smart grids etc. We frame the problems as average cost Markov decision processes. While the studied system is a linear system with quadratic costs, it has state dependent control and non-standard cost function structure, rendering the optimization problem complex. We obtain explicit optimal policies in the case when all the jobs are of same size. In particular, we show that the optimal policy is linear or piece-wise linear in the system state, depending on the system parameters. Further, when the job sizes can take two distinct values, we provide an algorithm that yields the optimal policy. We illustrate different forms of these policies via numerical examples.

In this paper, we evolve a methodology and define a metric to evaluate Tactile Cyber-Physical Systems (TCPS). Towards this goal, we adopt the step response analysis, a well-known control theoretic method. The adoption includes replacing the human operator (or master) with a controller with known characteristics and analyzing its response to slave side haptic sensor step changes. The resulting step response curves demonstrate that the Quality of Control (QoC) metric is sensitive to control loop instabilities and serves as a good indicator of cybersickness experienced by human operators. We demonstrate the efficacy of the proposed methodology and metric through experiments on a TCPS testbed. The experiments include assessing the suitability of several access technologies, intercontinental links and testbed configurations.

We propose a class of binary queue length information based max-weight scheduling algorithms for wireless networks. In these algorithms, the scheduler, in addition to channel states, only needs to know when a link's queue length crosses a prescribed threshold. We show that these algorithms are throughput optimal. Further, we incorporate time-since-last-service (TSLS) information to improve delay and service regularity of the scheduling algorithms while ensuring throughput optimality. We also perform simulations to illustrate throughput, delay and service regularity performance of the proposed algorithms.

We study stability properties of single-source single-destination delay tolerant networks with random packet arrivals and buffered relay nodes, using source spray and wait routing. We derive the stability threshold, the supremum of arrival rates for which the source queue is stable, as a function of the buffer space at the relays. In particular, we show that the stability threshold only doubles as the relays' buffer size increases from one to infinity for a network without packet delivery feedback. For the system without packet delivery feedback, we propose lower bounds for the average queueing delay and average delivery delay for packets and compare with simulations. We also obtain the stability threshold numerically for a network with instantaneous packet delivery feedback.

We study an offloading mechanism for cellular networks in which mobiles with good cellular links can act as hotspots and can assist other mobiles. We study throughput optimal offloading and also a fair offloading strategy which we call proportional increment offloading. We show that the former problem can be reduced to a capacitated facility location problem (CFLP) whereas the latter can be solved by solving a sequence of CFLPs. We propose a belief propagation based algorithm to solve CFLP, a well known NP complete problem. We primarily consider point coordination function (PCF) based WiFi access for offloading but also discuss distributed coordination function (DCF) based access and related issues. Further, we argue that all the mobiles benefit through participating in offloading. We perform extensive simulation to evaluate the performance of the proposed algorithms and effectiveness of mobile assisted offloading.

The proportionally fair sharing of the capacity of a Poisson network using Spatial-Aloha leads to closed-form performance expressions in two extreme cases: (1) the case without topology information, where the analysis boils down to a parametric optimization problem leveraging stochastic geometry; (2) the case with full network topology information, which was recently solved using shot-noise techniques. We show that there exists a continuum of adaptive controls between these two extremes, based on local stopping sets, which can also be analyzed in closed form. We also show that these control schemes are implementable, in contrast to the full information case which is not. As local information increases, the performance levels of these schemes are shown to get arbitrarily close to those of the full information scheme. The analytical results are combined with discrete event simulation to provide a detailed evaluation of the performance of this class of medium access controls.

LP relaxations of Maximum Weighted Independent Set (MWIS) problems have been widely studied. A key motivation for this prior work comes from the central role that MWIS plays in designing throughput-optimal algorithms for wireless networks. However, to the best of our knowledge, the actual packet delay performance of these algorithms has not been studied in the context of wireless networks. In this paper, we first present an algorithm for solving the LP relaxation of MWIS which exhibits faster convergence to an optimal solution. Further, we show that one does not have to wait for infinite time for convergence to occur, but a simple rounding technique can be used to identify the ON/OFF states of the wireless links in finite time. As in prior work, such an approach only identifies the optimal MWIS states of some of the links in the network. Therefore, we present a scheme to combine this solution with Q-CSMA. Simulations indicate that the proposed scheme significantly improves the performance of Q-CSMA. Further, the proposed algorithm is shown to perform much better than previously suggested LP relaxation schemes due to its superior convergence properties.