This paper analyzes the Age of Information (AoI), focusing on transmitting status updates from source to destination. We analyze the Age of Information in a system comprised of two heterogeneous servers with exponential distribution parameters$\mu _{1}$and$\mu _{2}$, respectively. Our study adopts the stochastic hybrid systems (SHS) methodology to thoroughly assess the system’s performance. We explore various queueing disciplines, including Last-Come-First-Serve (LCFS) with work-conservative and LCFS with probabilistic routing, to accurately quantify AoI and Peak AoI (PAoI) metrics. We have used the Proactive Obsolete Packet Management (POPMAN) approach to identify and discard obsolete packets proactively, thus enhancing server processing efficiency and ensuring orderly packet reception. We also investigate the following parameters, such as the probability of preemption of packets, the probability of packets getting obsolete, the probability of informative packets, and optimal splitting probabilities. Results show an improvement in both AoI and PAoI within the LCFS with work-conservative queueing system with the integration of the POPMAN method. Furthermore, LCFS with probabilistic routing using the POPMAN approach performs similarly to conventional methods. In all the queueing systems studied, as the arrival rate$\lambda \to \infty$, the average AoI and PAoI approach$1/(\mu _{1}+\mu _{2})$. For c servers, they approach$1/(\mu _{1}+\mu _{2}+\cdots +\mu _{c})$.

A longstanding problem in the context of computer networks is the issue of recovery from link failures. A promising solution to safeguard all single link failures (SLF) is through partial up gradation of certain IP routers (Internet Protocol(IP)) to Software Defined Networking (SDN) switches using CSA (Candidate Selection Algorithms). The resultant network comprises a combination of IP routers and SDN switches, forming a hybrid IP/SDN network. Most of the existing approaches primarily address SLFs, yet real-world scenarios may involve multiple link failures (MLF). Hence, it’s crucial to investigate CSA for Hybrid IP/SDN with MLF. In this paper, we first introduce four CSA strategies tailored for hybrid IP/SDN networks with MLF. Subsequently, we present a CSA designed to accommodate network scaling or expansion. We emphasize the advantage of CSAs based on non-shortest path approach. Additionally, we propose a budget constraint-based CSA to aid in selecting suitable candidate switches within a specified budget. We evaluate the performance of hybrid IP/SDN networks employing the proposed CSAs, considering average repair path length (AMLU) and average maximum link utilization (AMLU) in the post-recovery network across diverse real-world network topologies. It will be shown that the hybrid IP/SDN with proposed CSA for MLFs will reduce the ARPL by 31.37%, 22.15%, and 18.64%, respectively, for NSF, Attmpls, and Abilene networks.

Efficient medium access protocols are crucial in leveraging the advancement in the physical layer techniques that have been proposed for the next-generation wireless networks. However, collisions among data packets in random access protocols reduce channel efficiency and hence the throughput. In this paper, we propose a MAC protocol based on both the signal transmission diversity and Successive interference cancellation (SIC) to improve the throughput. In the proposed Medium Access Control (MAC) protocol, the receiver receives two sets of signals from the transmitters over two uncorrelated time slots. Inter slot SIC is first carried out at the receiver over two independent sets of received interfered signals. Signals are decoded by canceling those signals that have already been decoded in one set from the other set. Closed-form expressions for the packet decoding probability, system throughput, average packet transmission delay, and energy efficiency have been derived by considering order statistics of received signal power . Analytical results are validated against simulation. Maximum achievable throughput of the proposed scheme is shown to be four times that of slotted Aloha and twice that of a slotted Aloha with SIC.

The trend towards multi-core and many-core processors has changed the landscape of computers and servers. Now the performance of a microprocessor heavily depends not only on the data path but also on the memory technology and communication technology. On-chip communication networks or Network-on-Chip is a component which facilitates communication between the cores of a microprocessor. In this manuscript we propose an analytical model for the analysis of Network-on-Chip performance based on Jackson queuing networks for applications that exhibit Poisson injection process. The injection process statistics and the traffic profile of PARSEC benchmarks have been characterized. We have shown that injection process of PARSEC benchmarks does not match with the well known probability distributions using Quantile-Quantile plot and Kolmogorov-Smirnov test. For realistic benchmarks that does not follow Poisson injection process we propose$G/D/1$queuing model for the NoC router. We have carried out performance analysis using the traffic characterization in conjunction with our analytical model for prediction of performance metrics. The analytical model offers a speed up of around 13 times in comparison with the simulation based performance evaluation. The percentage of error between the analytical model and simulation is less than 6% for most of the benchmarks except Canneal and Ferret. We have also compared our analytical model results with the results of SNIPER simulator.

Time slotted channel hopping (TSCH) is a mediumaccess control (MAC) protocol introduced in IEEE802.15.4e standard, addressing low-power requirements of the Internet of Things and low-power and lossy networks. The 6TiSCH operation (6top) sublayer of IEEE802.15.4e defines the schedule that includes sleep, transmit, and receive routines of the nodes. However, the standard does not specify the design of the schedule. In this article, we propose a contention-based proportional fairness transmission scheme for TSCH networks to maximize the system throughput addressing the fair allocation of resources to the nodes. We propose a convex programming-based method to achieve the fairness and throughput objectives. We model TSCH MAC as a multichannel slotted ALOHA and analyze it for a schedule given by the 6top layer. Performance metrics, such as throughput, delay, and energy spent per successful transmission, are derived and validated through simulations and real-time testbed implementations.

High demand for reliability, low latency, seamless connectivity lead to the 5G era. 5G cellular networks employ a random access based preamble transmission procedure for the initial locking of User Equipment (UEs) to a base station (gNB) and uplink resource scheduling. It is of utmost importance that we evaluate the factors that aid and those that limit the random access procedure in achieving its envisaged goal. In this paper, we develop an analytical model for random access procedure for connection establishment in 5G when beamforming is employed. The random access medium is modelled as a multi-channel slotted Aloha system. We use an equilibrium point analysis framework to derive the performance metrics namely, the rate at which UEs can lock on to a gNB and the average and variance of the time taken by a new UE to establish connection with the base station. We analyse the impact of the retransmission limit and the number of available preambles for random access on the performance of connection establishment of a UE. Our analysis brings out the importance of the choice of base station configurations with respect to the user demographics of a 5G NR cell.

Time Slotted Channel Hopping (TSCH) behavioural mode has been introduced in IEEE 802.15.4e standard to address the ultra-high reliability and ultra-low power communication requirements of Industrial Internet of Things (IIoT) networks. Scheduling the packet transmissions in IIoT networks is a difficult task owing to the limited resources and dynamic topology. In this paper, we propose a phasic policy gradient (PPG) based TSCH schedule learning algorithm. The proposed PPG based scheduling algorithm overcomes the drawbacks of totally distributed and totally centralized deep reinforcement learning-based scheduling algorithms by employing the actor-critic policy gradient method that learns the scheduling algorithm in two phases, namely policy phase and auxiliary phase.

IEEE 802.15.4e Time Slotted Channel Hopping (TSCH) standard has gained prominence in the Industrial Internet of Things (IIoT) research community due to its potency in improving reliability, providing low latency and low power consumption. In TSCH, a schedule orchestrates the communication in the networks between the nodes. The design and maintenance of the schedule are out of the standard's scope, and is open for implementation. In this paper, we address the design problem of an optimal scheduling algorithm in TSCH networks. We design a TSCH schedule inspired by a biogeographical aspect of bird flocking. Like bird flocks, which migrate to find a suitable habitat depending on several features like seasons, food availability, etc., a TSCH network can also end up in an optimal schedule for its dynamic requirements. With this motivation, we design a biogeography inspired optimal schedule (BIOS) for TSCH networks incorporating the features such as migration and mutation to learn the best schedule. We show that the proposed BIOS-TSCH schedule is also suited for the sporadic and dynamic networks. We evaluate the performance of BIOS-TSCH in terms of convergence, delay and radio duty cycle. We show that the proposed BIOS-TSCH schedule achieves an improvement of 60% in delay performance and up to 40% in energy efficiency compared to the minimal scheduling function.

Reuse distance has been shown to be a useful metric for performance analysis of caches and programs, locality analysis and compiler optimization. Concurrent reuse distance profile defined as the reuse distance profile of a thread sharing the cache with many other threads varies from its standalone reuse distance profile due to interference from other threads. Measurement of reuse distance profile through simulation, especially for multi-threaded applications, consumes lot of time. Analytical model based reuse distance prediction can reduce drastically the time taken for exploring the cache memory design space. The objective of this work is to propose an analytical model to find the concurrent reuse distance profile of a thread belonging to multi-threaded applications in a shared memory environment. Using the standalone reuse distance profile of each thread as input, we derive three other reuse distance profiles: 1) The concurrent reuse distance profile of a thread sharing the cache with other threads 2) The combined reuse distance profile of all threads sharing the cache and 3) The coherent reuse distance profile of each thread, considering the coherency effect when each thread runs with private cache. We use Markov chain besides combinatorics and basic probability theory as a main analytical tool for the model. We validate our analytical model against simulations, using the multi-core simulator Sniper for the benchmarks of the PARSEC and the SPLASH benchmark suites.

Reuse distance is an important metric for analytical estimation of cache miss rate. To find the miss rate of a particular cache, the reuse distance profile has to be measured for that particular level and configuration of the cache. Significant amount of simulation time and overhead can be reduced if we can find the miss rate of higher level cache like L2 cache from the RD profile with respect to a lower level cache (i.e., cache that is closer to the processor) such as L1. The objective of this paper is to give an analytical method to find the miss rate of L2 cache for various configurations from the RD profile with respect to L1 cache. We consider all three types of cache inclusion policies namely (i) Strictly Inclusive, (ii) Mutually Exclusive and (iii) Non-Inclusive Non-Exclusive policy. We first prove some general results relating the RD profile of L1 cache to that of L2 cache. We use probabilistic analysis for our derivations. We validate our model against simulations, using the multi-core simulator Sniper with the PARSEC and the SPLASH benchmark suites.

We consider a multichannel Cognitive Radio Network (CRN), where secondary users sequentially sense channels for opportunistic spectrum access. In this scenario, the Channel Selection Algorithm (CSA) allows secondary users to find a vacant channel with the minimal number of channel switches. Most of the existing CSA literature assumes exponential ON-OFF time distribution for primary user's (PU) channel occupancy pattern. This exponential assumption might be helpful to get performance bounds; but not useful to evaluate the performance of CSA under realistic conditions. An in-depth analysis of independent spectrum measurement traces reveals that wireless channels have typically heavy-tailed PU OFF times. In this paper, we propose an extension to the Predictive CSA framework and its generalization for heavy tailed PU OFF time distribution, which represents realistic scenarios. In particular, we calculate the probability of channel being idle for hyper-exponential OFF times to use in CSA. We implement our proposed CSA framework in a wireless test-bed and comprehensively evaluate its performance by recreating the realistic PU channel occupancy patterns. The proposed CSA shows significant reduction in channel switches and energy consumption as compared to Predictive CSA which always assumes exponential PU ON-OFF times. Through our work, we show the impact of the PU channel occupancy pattern on the performance of CSA in multichannel CRN.

We consider a Machine-to-Machine (M2M) network where a large number of user nodes (STAs) communicate with a Data Collector (DC). We consider the case where all the user nodes periodically transmit their data packets to the DC and the network is in saturation. Recently protocols based on Frame Slotted Aloha (FSA) have been shown to be suitable as MAC protocols for M2M data collection networks under saturated conditions. It can be shown that implementing Multi-Packet Reception (MPR) capability to the DC improves the performance of the FSA protocol. In this work we propose a Multi-Packet Reception (MPR) based FSA (MPR-FSA) protocol and study its performance. We derive the asymptotic limits of throughput, delay and energy efficiency based on MPR-FSA protocol. We also derive the limiting value of MPR (Klim) parameter for a given FSA based data collection network at which asymptotic performance is achieved. A mathematical model is proposed and the analytical values are validated using extensive simulations.

We present an analytical model for the access during the Service Periods (SP) of the IEEE 802.11ad Hybrid Medium Access Control protocol. As a performance measure of this protocol, we derive the worst case and average delay faced by the SP packets. We show that as the arrival rate of the SP packets increases, the delay increases linearly till a point, beyond which it grows exponentially. Further, we extend the model to variable length of beacon interval, and random allocation of SPs to the nodes. We show how a network designer can do optimal allocation of the SP and the CBAP duration to achieve a tradeoff between SP delay and CBAP throughput. We further extend our analysis for the case of heterogeneous system. Our analytical results are compared with simulation and the results show a good match.

Exact throughput analysis of unslotted carrier sense multiple access (CSMA) protocols for channels supporting multi‐packet reception (MPR) is carried out. The protocols considered include (i) non‐persistent and (ii) 1‐persistent CSMA. An adaptive non‐persistent CSMA protocol for channels supporting MPR has been proposed and evaluated. A Markov chain model with states representing the transmission period of the 1‐persistent CSMA is used in the analysis. Analytical results are validated using simulation. The authors show that for CSMA protocols supporting MPR the throughput is crucially dependent on the carrier sensing delay.