A Survey on Delay-Aware Resource Control for Wireless Systems --- Large Deviation Theory, Stochastic Lyapunov Drift and Distributed Stochastic Learning

In this tutorial paper, a comprehensive survey is given on several major systematic approaches in dealing with delay-aware control problems, namely the equivalent rate constraint approach, the Lyapunov stability drift approach and the approximate Markov Decision Process (MDP) approach using stochastic learning. These approaches essentially embrace most of the existing literature regarding delay-aware resource control in wireless systems. They have their relative pros and cons in terms of performance, complexity and implementation issues. For each of the approaches, the problem setup, the general solution and the design methodology are discussed. Applications of these approaches to delay-aware resource allocation are illustrated with examples in single-hop wireless networks. Furthermore, recent results regarding delay-aware multi-hop routing designs in general multi-hop networks are elaborated. Finally, the delay performance of the various approaches are compared through simulations using an example of the uplink OFDMA systems.Comment: 58 pages, 8 figures; IEEE Transactions on Information Theory, 201

Combined use of prioritized AIMD and flow-based traffic splitting for robust TCP load balancing

Cataloged from PDF version of article.In this thesis, we propose a multi-path TCP load balancing traffic engineering methodology in IP networks. In this architecture, TCP traffic is split at the flow level between the primary and secondary paths in order to prevent the adverse effect of packet reordering on TCP performance occuring in packet-based load balancing schemes. Traffic splitting is done by using a random early rerouting algorithm that controls the queuing delay difference between the two alternative paths. We apply strict priority queuing in order to prevent the knock-on effect that arises when primary and secondary path queues have equal priority. Probe packets are used for getting congestion information from the output queues of links along the paths and AIMD (Additive Increase/Multiplicative Decrease) based rate control using this congestion information is applied to the traffic routed over these paths. We compare two queuing architectures, namely first-in-first-out (FIFO) and strict priority. We show through simulations that strict priority queuing has higher performance, it is relatively more robust than FIFO queuing and it eliminates the knock-on effect. We show that avoiding packet reordering by flow level splitting significantly improves the performance of long flows. The capabilities of ns-2 simulator is improved bu using optimizations in order to apply the simulator to relatively large networks. We show that incorporating a-priori knowledge of the traffic demand matrix into the proposed architecture can further improve its performance in terms of load balancing and byte rejection ratio.Alparslan, OnurM.S

Conservation Laws, Extended Polymatroids and Multi-Armed Bandit Problems; A unified Approach to Indexabel Systems

We show that if performance measures in stochastic and dynamic scheduling problems satisfy generalized conservation laws, then the feasible space of achievable performance is a polyhedron called an extended polymatroid that generalizes the usual polymatroids introduced by Edmonds. Optimization of a linear objective over an extended polymatroid is solved by an adaptive greedy algorithm, which leads to an optimal solution having an indexability property (indexable systems). Under a certain condition, then the indices have a stronger decomposition property (decomposable systems). The following classical problems can be analyzed using our theory: multi-armed bandit problems, branching bandits. multiclass queues, multiclass queues with feedback, deterministic scheduling problemls. Interesting consequences of our results include: (1) a characterization of indexable systems as systems that satisfy generalized conservation laws, (2) a. sufficient condition for idexable systems to be decomposable, (3) a new linear programming proof of the decomposability property of Gittins indices in multi-armed bandit problems, (4) a unified and practical approach to sensitivity analysis of indexable systems, (5) a new characterization of the indices of indexable systems as sums of dual variables and a new interpretation of the indices in terms of retirement options in the context of branching bandits, (6) the first rigorous analysis of the indexability of undiscounted branching bandits, (7) a new algorithm to compute the indices of indexable systems (in particular Gittins indices), which is as fast as the fastest known algorithm, (8) a unification of the algorithm of Klimov for multiclass queues and the algorithm of Gittins for multi-armed bandits as special cases of the same algorithm. (9) closed form formulae for the performance of the optimal policy, and (10) an understanding of the nondependence of the indices on some of the parameters of the stochastic schediiuling problem. Most importantly, our approach provides a unified treatment of several classical problems in stochastic and dynamic scheduling and is able to address in a unified way their variations such as: discounted versus undiscounted cost criterion, rewards versus taxes. preemption versus nonpreemption, discrete versus continuous time, work conserving versus idling policies, linear versus nonlinear objective functions

Multi-threshold Control of the BMAP/SM/1/K Queue with Group Services

We consider a finite capacity queue in which arrivals occur according to a batch Markovian arrival process (BMAP). The customers are served in groups of varying sizes. The services are governed by a controlled semi-Markovian process according to a multithreshold strategy. We perform the steady-state analysis of this model by computing (a) the queue length distributions at departure and arbitrary epochs, (b) the Laplace-Stieltjes transform of the sojourn time distribution of an admitted customer, and (c) some selected system performance measures. An optimization problem of interest is presented and some numerical examples are illustrated

Self-Evaluation Applied Mathematics 2003-2008 University of Twente

This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008

Bi-objective optimization of the tactical allocation of job types to machines: mathematical modeling, theoretical analysis, and numerical tests

We introduce a tactical resource allocation model for a large aerospace engine system manufacturer aimed at long-term production planning. Our model identifies the routings a product takes through the factory, and which machines should be qualified for a balanced resource loading, to reduce product lead times. We prove some important mathematical properties of the model that are used to develop a heuristic providing a good initial feasible solution. We propose a tailored approach for our class of problems combining two well-known criterion space search algorithms, the bi-directional ε-constraint method and the augmented weighted Tchebycheff method. A computational investigation comparing solution times for several solution methods is presented for 60 numerical\ua0instances

Topics in access, storage, and sensor networks

In the first part of this dissertation, Data Over Cable Service Interface Specification (DOCSIS) and IEEE 802.3ah Ethernet Passive Optical Network (ETON), two access networking standards, are studied. We study the impact of two parameters of the DOCSIS protocol and derive the probability of message collision in the 802.3ah device discovery scheme. We survey existing bandwidth allocation schemes for EPONs, derive the average grant size in one such scheme, and study the performance of the shortest-job-first heuristic. In the second part of this dissertation, we study networks of mobile sensors. We make progress towards an architecture for disconnected collections of mobile sensors. We propose a new design abstraction called tours which facilitates the combination of mobility and communication into a single design primitive and enables the system of sensors to reorganize into desirable topologies alter failures. We also initiate a study of computation in mobile sensor networks. We study the relationship between two distributed computational models of mobile sensor networks: population protocols and self-similar functions. We define the notion of a self-similar predicate and show when it is computable by a population protocol. Transition graphs of population protocols lead its to the consideration of graph powers. We consider the direct product of graphs and its new variant which we call the lexicographic direct product (or the clique product). We show that invariants concerning transposable walks in direct graph powers and transposable independent sets in graph families generated by the lexicographic direct product are uncomputable. The last part of this dissertation makes contributions to the area of storage systems. We propose a sequential access detect ion and prefetching scheme and a dynamic cache sizing scheme for large storage systems. We evaluate the cache sizing scheme theoretically and through simulations. We compute the expected hit ratio of our and competing schemes and bound the expected size of our dynamic cache sufficient to obtain an optimal hit ratio. We also develop a stand-alone simulator for studying our proposed scheme and integrate it with an empirically validated disk simulator

Scalable String and Suffix Sorting: Algorithms, Techniques, and Tools

This dissertation focuses on two fundamental sorting problems: string sorting and suffix sorting. The first part considers parallel string sorting on shared-memory multi-core machines, the second part external memory suffix sorting using the induced sorting principle, and the third part distributed external memory suffix sorting with a new distributed algorithmic big data framework named Thrill.Comment: 396 pages, dissertation, Karlsruher Instituts f\"ur Technologie (2018). arXiv admin note: text overlap with arXiv:1101.3448 by other author