Age-Optimal Updates of Multiple Information Flows

In this paper, we study an age of information minimization problem, where multiple flows of update packets are sent over multiple servers to their destinations. Two online scheduling policies are proposed. When the packet generation and arrival times are synchronized across the flows, the proposed policies are shown to be (near) optimal for minimizing any time-dependent, symmetric, and non-decreasing penalty function of the ages of the flows over time in a stochastic ordering sense

String Method for Generalized Gradient Flows: Computation of Rare Events in Reversible Stochastic Processes

Rare transitions in stochastic processes can often be rigorously described via an underlying large deviation principle. Recent breakthroughs in the classification of reversible stochastic processes as gradient flows have led to a connection of large deviation principles to a generalized gradient structure. Here, we show that, as a consequence, metastable transitions in these reversible processes can be interpreted as heteroclinic orbits of the generalized gradient flow. This in turn suggests a numerical algorithm to compute the transition trajectories in configuration space efficiently, based on the string method traditionally restricted only to gradient diffusions

Specifying and Placing Chains of Virtual Network Functions

Network appliances perform different functions on network flows and constitute an important part of an operator's network. Normally, a set of chained network functions process network flows. Following the trend of virtualization of networks, virtualization of the network functions has also become a topic of interest. We define a model for formalizing the chaining of network functions using a context-free language. We process deployment requests and construct virtual network function graphs that can be mapped to the network. We describe the mapping as a Mixed Integer Quadratically Constrained Program (MIQCP) for finding the placement of the network functions and chaining them together considering the limited network resources and requirements of the functions. We have performed a Pareto set analysis to investigate the possible trade-offs between different optimization objectives

Opportunistic Relaying in Time Division Broadcast Protocol with Incremental Relaying

In this paper, we investigate the performance of time division broadcast protocol (TDBC) with incremental relaying (IR) when there are multiple available relays. Opportunistic relaying (OR), i.e., the “best” relay is select for transmission to minimize the system’s outage probability, is proposed. Two OR schemes are presented. The first scheme, termed TDBC-OIR-I, selects the “best” relay from the set of relays that can decode both flows of signal from the two sources successfully. The second one, termed TDBC-OIR-II, selects two “best” relays from two respective sets of relays that can decode successfully each flow of signal. The performance, in terms of outage probability, expected rate (ER), and diversity-multiplexing tradeoff (DMT), of the two schemes are analyzed and compared with two TDBC schemes that have no IR but OR (termed TDBC-OR-I and TDBC-OR-II accordingly) and two other benchmark OR schemes that have no direct link transmission between the two sources