132 research outputs found
Model-Predictive Control in Communication Networks
This dissertation consists of 8 papers, separated into 3 groups. The first 3 papers show, how model-predictive control can be applied to queueing networks and contain a detailed proof of throughput optimality. Additionally, numerous network examples are discussed, and a connection between the stability properties of assembly queues and random walks on quotient spaces is established. The next two papers develop algorithms, with which robust forecasts of delay can be obtained in queueing networks. To that end, a notion of robustness is proposed, and the network control policy is designed to meet this goal. For the last 3 papers, focus is shifted towards Age-of-Information. Two main contributions are the derivation of the distribution of the Age-of-Information values in networks with clocked working cycles and an algorithm for the exact numerical evaluation of the Age-of-Information state-space in a similar set-up
Stability Problems for Stochastic Models: Theory and Applications II
Most papers published in this Special Issue of Mathematics are written by the participants of the XXXVI International Seminar on Stability Problems for Stochastic Models, 21Â25 June, 2021, Petrozavodsk, Russia. The scope of the seminar embraces the following topics: Limit theorems and stability problems; Asymptotic theory of stochastic processes; Stable distributions and processes; Asymptotic statistics; Discrete probability models; Characterization of probability distributions; Insurance and financial mathematics; Applied statistics; Queueing theory; and other fields. This Special Issue contains 12 papers by specialists who represent 6 countries: Belarus, France, Hungary, India, Italy, and Russia
Stability and partial instability of multi-class retrial queues
International audienc
Performance analysis of redundancy and mobility in multi-server systems
In this thesis, we studied how both redundancy and mobility impact the performance of computer systems and cellular networks, respectively. The general notion of redundancy is that upon arrival each job dispatches copies into multiple servers. This allows exploiting the variability of the queue lengths and server capacities in the system. We consider redundancy models with both identical and i.i.d. copies. When copies are i.i.d., we show that with PS and ROS, redundancy does not reduce the stability region. When copies are identical, we characterize the stability condition for systems where either FCFS, PS, or ROS is implemented in the servers. We observe that this condition strongly depends on the scheduling policy implemented in the system. We then investigate how redundancy impacts the performance by comparing it to a non-redundant system. We observe that both the stability and performance improve considerably under redundancy as the heterogeneity of the server capacities increases. Furthermore, for both i.i.d. and identical copies, we characterize redundancy-aware scheduling policies that improve both the stability and performance. Finally, we identify several open problems that might be of interest to the community. User mobility in wireless networks addresses the fact that users in a cellular network switch from cell to cell when geographically moving in the system. We control the mobility speed of the users among the servers and analyze how mobility impacts the performance at a user level. We observe that the performance of the system under fixed mobility speed strongly depends on the inherent parameters of the system
Age of Information Optimization for Timeliness in Communication Networks
With the emergence of technologies such as autonomous vehicular systems, holographic communications, remote surgery and high frequency automated trading, timeliness of information has become more important than ever. Most traditional performance metrics, such as delay or throughput, are not sufficient to measure timeliness. For that, age of information (AoI) has been introduced recently as a new performance metric to quantify the timeliness in communication networks. In this dissertation, we consider timely update delivery problems in communication networks under various system settings.
First, we introduce the concept of soft updates, where different from the existing literature, here, updates are soft and begin reducing the age immediately but drop it gradually over time. Our setting models human interactions where updates are soft, and also social media interactions where an update consists of viewing and digesting many small pieces of information posted, that are of varying importance, relevance and interest to the receiver. For given total system duration, the number of updates, and the total allowed update duration, we find the optimum start times of the soft updates and their optimum durations to minimize the overall age.
Then, we consider an information updating system where not only the timeliness but also the quality of the updates is important. Here, we use distortion as a proxy for quality, and model distortion as a decreasing function of processing time spent while generating the updates. Processing longer at the transmitter results in a better quality (lower distortion) update, but it causes the update to age in the process. We determine age-optimal policies by characterizing the update request times at the receiver and the update processing times at the transmitter subject to constant or age-dependent distortion constraints on each update.
Next, different from most of the existing literature on AoI where the transmission times are based on a given distribution, by assigning codeword lengths for each status update, we design transmission times through source coding schemes. In order to further improve timeliness, we propose selective encoding schemes where only the most probable updates are transmitted. For the remaining least probable updates, we consider schemes where these updates are never sent, randomly sent, or sent by an empty symbol. For all these encoding schemes, we determine the optimal number of encoded updates and their corresponding age-optimal real-valued codeword lengths to minimize the average age at the receiver.
Then, we study the concept of generating partial updates which carry less information compared to the original updates, but their transmission times are shorter. Our aim is to find the age-optimal partial update generation process and the corresponding age-optimal real-valued codeword lengths for the partial updates while maintaining a desired level of fidelity between the original and partial updates.
Next, we consider information freshness in a cache updating system consisting of a source, cache(s) and a user. Here, the user may receive an outdated file depending on the freshness status of the file at the cache. We characterize the binary freshness metric at the end user and propose an alternating maximization based method to optimize the overall freshness at the end user subject to total update rate constraints at the cache(s) and the user.
Then, we study a caching system with a limited storage capacity for the cache. Here, the user either gets the files from the cache, but the received files can be sometimes outdated, or gets fresh files directly from the source at the expense of additional transmission times which inherently decrease the freshness. We show that when the total update rate and the storage capacity at the cache are limited, it is optimal to get the frequently changing files and files with relatively small transmission times directly from the source, and store the remaining files at the cache.
Next, we focus on information freshness in structured gossip networks where in addition to the updates obtained from the source, the end nodes share their local versions of the updates via gossiping to further improve freshness. By using a stochastic hybrid systems (SHS) approach, we determine the information freshness in arbitrarily connected gossip networks. When the number of nodes gets large, we find the scaling of information freshness in disconnected, ring and fully connected network topologies. Further, we consider clustered gossip networks where multiple clusters of structured gossip networks are connected to the source through cluster heads, and find the optimal cluster sizes numerically.
Then, we consider the problem of timely tracking of multiple counting random processes via exponential (Poisson) inter-sampling times, subject to a total sampling rate constraint. A specific example is how a citation index such as Google Scholar should update citation counts of individual researchers to keep the entire citation index as up-to-date as possible. We model citation arrival profile of each researcher as a counting process with a different mean, and consider the long-term average difference between the actual citation numbers and the citation numbers according to the latest updates as a measure of timeliness. We show that, in order to minimize this difference metric, Google Scholar should allocate its total update capacity to researchers proportional to the square roots of their mean citation arrival rates.
Next, we consider the problem of timely tracking of multiple binary random processes via sampling rate limited Poisson sampling. As a specific example, we consider the problem of timely tracking of infection status (e.g., covid-19) of individuals in a population. Here, a health care provider wants to detect infected and recovered people as quickly as possible. We measure the timeliness of the tracking process as the long term average difference between the actual infection status of people and their real-time estimate at the health care provider which is based on the most recent test results. For given infection and recovery rates of individuals, we find the exponentially applied testing rates for individuals to minimize this difference. We observe that when the total test rate is limited, instead of applying tests to everyone, only a portion of the population should be tested.
Finally, we consider a communication system with multiple information sources that generate binary status updates, which in practical application may indicate an anomaly (e.g., fire) or infection status (e.g., covid-19). Each node exhibits an anomaly or infection with probability . In order to send the updates generated by these sources as timely as possible, we propose a group updating method inspired by group testing, but with the goal of minimizing the overall average age, as opposed to the average number of tests (updates). We show that when the probability is small, group updating method achieves lower average age than the sequential updating methods
Transmission Scheduling in Wireless Networked Control for Industrial IoT
Wireless networked control systems (WNCS) consist of spatially distributed sensors, actuators, and controllers communicating through wireless networks. WNCS has recently emerged as a fundamental infrastructure technology to enable reliable control for mission-critical Industrial Internet of Things (IIoT) applications such as factory automation, intelligent transportation systems, telemedicine and smart grids. The design of WNCS requires the joint design of communications, computing and control. WNCS faces challenges such as unreliable transmission and latency in transmitting control and sensing information due to channel impairment in wireless communications for large scale deployment. This can have a significant impact on the stability and performance of WNCS. Most existing works have mainly focused on the design of WNCS from a control perspective rather than communications or have considered an ideal or simplified wireless model. How to reliably control WNCS in practical wireless channels and design wireless communication scheduling policy to optimize control performance is a challenging task.
This thesis presents the design of practical communication protocols of a general discrete linear time-invariant (LTI) dynamic system in WNCS. We address the transmission scheduling problems in WNCS in three scenarios, which require the development of different strategies. Firstly, to minimize the long-term average remote estimation mean-squared-error (MSE), a hybrid automatic repeat request (HAQR)-based real-time estimation framework is proposed. Secondly, a downlink-uplink transmission scheduling policy is developed for a half-duplex (FD) controller to optimize the system performance.
Finally, a novel controller with adaptive packet length is studied, and a variable-length packet-transmission policy is proposed to balance the delay-reliability tradeoff in WNCS optimally. Numerical results show that our dynamic scheduling policies can significantly improve the performance of WNCS in terms of estimation and control costs while maintaining the stability of the system
Game Theory Relaunched
The game is on. Do you know how to play? Game theory sets out to explore what can be said about making decisions which go beyond accepting the rules of a game. Since 1942, a well elaborated mathematical apparatus has been developed to do so; but there is more. During the last three decades game theoretic reasoning has popped up in many other fields as well - from engineering to biology and psychology. New simulation tools and network analysis have made game theory omnipresent these days. This book collects recent research papers in game theory, which come from diverse scientific communities all across the world; they combine many different fields like economics, politics, history, engineering, mathematics, physics, and psychology. All of them have as a common denominator some method of game theory. Enjoy
Emerging Communications for Wireless Sensor Networks
Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing devices that are becoming ever more pervasive in our interconnected society. This book presents a range of exciting developments in software communication technologies including some novel applications, such as in high altitude systems, ground heat exchangers and body sensor networks. Authors from leading institutions on four continents present their latest findings in the spirit of exchanging information and stimulating discussion in the WSN community worldwide
Internet of Things and Sensors Networks in 5G Wireless Communications
The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic
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