We describe a first principles based integrated modeling environment to study urban socio-communication networks which represent not just the physical cellular communication network, but also urban populations carrying digital devices interacting with the cellular network. The modeling environment is designed specifically to understand spectrum demand and dynamic cellular network traffic. One of its key features is its ability to support individual-based models at highly resolved spatial and temporal scales. We have instantiated the modeling environment by developing detailed models of population mobility, device ownership, calling patterns and call network. By composing these models using an appropriate in-built workflow, we obtain an integrated model that represents a dynamic socio-communication network for an entire urban region. In contrast with earlier papers that typically use proprietary data, these models use open source and commercial data sets. The dynamic model represents for a normative day, every individual in an entire region, with detailed demographics, a minute-by-minute schedule of each person's activities, the locations where these activities take place, and calling behavior of every individual. As an illustration of the applicability of the modeling environment, we have developed such a dynamic model for Portland, Oregon comprising of approximately 1.6 million individuals. We highlight the unique features of the models and the modeling environment by describing three realistic case studies.

Large scale realistic simulations of malware on mobile wireless networks have recently become an increasingly important application of high-performance computing. We propose EpiCure - an individual-based, scalable high performance computing oriented modeling environment to study malware propagation over realistic mobile networks. It is designed specifically to work on commodity cluster architectures. EpiCure runs extremely fast for realistic instances that involve: (i) large time-varying networks consisting of millions of heterogeneous individuals with time varying interaction neighborhoods, (ii) dynamic interactions between disease propagation, device behavior, and the exogenous interventions, and (iii) large number of replicated runs necessary for statistically sound estimates about the stochastic epidemic evolution. We find that EpiCure runs several orders of magnitude faster than another comparable simulation tool while delivering similar results. Beyond simple compute speed, EpiCure has been designed so that analysts can easily represent a range of interventions leading to improved human productivity and ease of use. This is an increasingly important metric in high performance computing. We illustrate EpiCure using three case studies that bring out the novel features of EpiCure.

We consider real-time CORBA 1.2 (dynamic scheduling) distributable threads operating in multihop networks. When distributable threads are subject to time/utility function-time constraints, and timeliness optimality criteria such as maximizing accrued system-wide utility is desired, utility accrual real-time channels must be established. Such channels transport messages that are generated as distributable threads transcend nodes, in a way that maximizes system-wide, message-level utility. We present 1) a localized utility accrual channel establishment algorithm called localized decision for utility accrual channel establishment (or LocDUCE) and 2) a distributed utility accrual channel establishment algorithm called global decision for utility accrual channel establishment (or GloDUCE). Since the channel establishment problem is NP-complete. LocDUCE and GloDUCE heuristically compute channels, with LocDUCE making decisions based on local information pertaining to the node and GloDUCE making global decisions. We simulate the performance of the algorithms and compare them with the open shortest path first (OSPF) routing algorithm and the optimal algorithm. We also implement these algorithms in a prototype testbed and experimentally compare their performance with OSPF. Our simulation and experimental measurements reveal that GloDUCE and LocDUCE accrue significantly higher utility than OSPF and also perform close to the optimal for some cases. Furthermore, GloDUCE outperforms LocDUCE under high downstream traffic.

Recent advances in dynamic power management (DPM) techniques have resulted in designs that support a rich set of power management options, both at the hardware and software levels. This has resulted in an explosion of the design space when analyzing the system-level tradeoffs of candidate DPM strategy designs. This paper proposes a design space exploration methodology based on a high-level, multi-layered modeling framework that facilitates rapid estimation of system-wide energy by providing the designer with a global view of the system. The framework is based on the extended finite state machine formalism and abstracts the component power modes, the operating environment and the DPM architecture into interacting, concurrent layers within a single, unified model. The modeling framework is coupled with a symbolic simulation engine to allow for rapid traversal of the large design space. We first illustrate how the proposed model can be constructed by making reasonable assumptions on the system and workload parameters, and then we show how analysis of various candidate strategies can be performed using this model. Our aim is to provide a high-level model that can be used to quickly assess the impact of various power management decisions on the system-wide energy. The framework can also be a formal basis for design of energy efficient power management systems.

We consider real-time CORBA 2.0 (dynamic scheduling) distributable threads operating in multihop networks. When distributable threads are subject to time/utility function-time constraints and utility accrual optimality criteria, utility accrual real-time channels must be established. Such channels transport inter-node messages of distributable threads in a way that maximizes system-wide, message-level accrued utility. We present a utility accrual channel establishment algorithm called local decision for utility accrual channel establishment (or Loc-DUCE) that heuristically computes channels. Our experimental measurements using a prototype implementation reveal that LocDUCE accrues significantly higher utility than the open shortest path first routing algorithm