Abstract-System-centric modeling and analysis are of key significance in planning and optimizing cellular networks. In this paper, we provide a mathematical analysis of performance modeling for LTE networks. The system model characterizes the coupling relation between the cell load factors, taking into account non-uniform traffic demand and interference between the cells with arbitrary network topology. Solving the model enables a network-wide performance evaluation in resource consumption. We develop and prove both sufficient and necessary conditions for the feasibility of the load-coupling system, and provide results related to computational aspects for numerically approaching the solution. The theoretical findings are accompanied with experimental results to instructively illustrate the application in optimizing LTE network configuration.

Abstract-A promising multi-user access scheme, nonorthogonal multiple access (NOMA) with successive interference cancellation (SIC), is currently under consideration for 5G systems. NOMA allows more than one user to simultaneously access the same frequency-time resource and separates multi-user signals by SIC. These render resource optimization in NOMA different from orthogonal multiple access. We provide theoretical insights and algorithmic solutions to jointly optimize power and channel allocation in NOMA. We mathematically formulate NOMA resource allocation problems, and characterize and analyze the problems' tractability under a range of constraints and utility functions. For tractable cases, we provide polynomial-time solutions for global optimality. For intractable cases, we prove the NP-hardness and propose an algorithmic framework combining Lagrangian duality and dynamic programming (LDDP) to deliver near-optimal solutions. To gauge the performance of the solutions, we also provide optimality bounds on the global optimum. Numerical results demonstrate that the proposed algorithmic solution can significantly improve the system performance in both throughput and fairness over orthogonal multiple access as well as over a previous NOMA resource allocation scheme.

Similar to software bugs, configuration errors are also one of the major causes of today's system failures. Many configuration issues manifest themselves in ways similar to software bugs such as crashes, hangs, silent failures. It leaves users clueless and forced to report to developers for technical support, wasting not only users' but also developers' precious time and effort. Unfortunately, unlike software bugs, many software developers take a much less active, responsible role in handling configuration errors because "they are users' faults."This paper advocates the importance for software developers to take an active role in handling misconfigurations. It also makes a concrete first step towards this goal by providing tooling support to help developers improve their configuration design, and harden their systems against configuration errors. Specifically, we build a tool, called SPEX, to automatically infer configuration requirements (referred to as constraints) from software source code, and then use the inferred constraints to: (1) expose misconfiguration vulnerabilities (i.e., bad system reactions to configuration errors such as crashes, hangs, silent failures); and (2) detect certain types of errorprone configuration design and handling.We evaluate SPEX with one commercial storage system and six open-source server applications. SPEX automatically infers a total of 3800 constraints for more than 2500 configuration parameters. Based on these constraints, SPEX further detects 743 various misconfiguration vulnerabilities and at least 112 error-prone constraints in the latest versions of the evaluated systems. To this day, 364 vulnerabilities and 80 inconsistent constraints have been confirmed or fixed by developers after we reported them. Our results have influenced the Squid Web proxy project to improve its configuration parsing library towards a more user-friendly design.

Abstract-Wireless communications using ad hoc networks are receiving an increasing interest. The most attractive feature of ad hoc networks is the flexibility. The network is set up by a number of units in an ad hoc manner, without the need of any fixed infrastructure. Communication links are established between two units if the signal strength is sufficiently high. As not all pairs of nodes can establish direct links, the traffic between two units may have to be relayed through other units. This is known as the multi-hop functionality.Design of ad hoc networks is a challenging task. In this paper we study the problem of resource allocation with spatial TDMA (STDMA) as the access control scheme. Previous work for this problem has mainly focused on heuristics, whose performance is difficult to analyze when optimal solutions are not known. We develop, for both node-oriented and link-oriented allocation strategies, mathematical programming formulations for resource optimization. We further present a column generation approach, which, in our numerical experiments, constantly yields optimal or near-optimal solutions. Our results provide important benchmarks when evaluating heuristic on-line algorithms for resource optimization using STDMA.Index Terms -Ad hoc networks, STDMA, node and link assignment, column generation

Abstract-We consider the problem of minimization of sum transmission energy in cellular networks where coupling occurs between cells due to mutual interference. The coupling relation is characterized by the signal-to-interference-and-noise-ratio (SINR) coupling model. Both cell load and transmission power, where cell load measures the average level of resource usage in the cell, interact via the coupling model. The coupling is implicitly characterized with load and power as the variables of interest using two equivalent equations, namely, non-linear load coupling equation (NLCE) and non-linear power coupling equation (NPCE), respectively. By analyzing the NLCE and NPCE, we prove that operating at full load is optimal in minimizing sum energy, and provide an iterative power adjustment algorithm to obtain the corresponding optimal power solution with guaranteed convergence, where in each iteration a standard bisection search is employed. To obtain the algorithmic result, we use the properties of the so-called standard interference function; the proof is non-standard because the NPCE cannot even be expressed as a closed-form expression with power as the implicit variable of interest. We present numerical results illustrating the theoretical findings for a real-life and large-scale cellular network, showing the advantage of our solution compared to the conventional solution of deploying uniform power for base stations.

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