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Abstract-In a recent paper, Bonald and Roberts [1] studied non-persistent TCP connections in transient overload conditions, under the assumption that all connections have the same round-trip times. In this paper our goal is to develop theoretical tools that will enable us to relax this assumption and obtain explicit expressions for the rate of growth of the number of connections at the system, the rate at which TCP connections leave the system, as well as the time needed for the completion of a connection. To that end, we model the system as a DPS (Discriminatory Processor Sharing) system which we analyze under very mild assumptions on the probability distributions related to different classes of arrivals: we only assume that the arrival rates of connections exist, and that the amount of information transmitted during a connection of a given type forms a stationary ergodic sequence. We then proceed to obtain explicit expressions for the growth rate of the number of connections at the DPS system for several specific probability distributions. We check through simulations the applicability of our queueing results for modeling TCP connections sharing a bottleneck.

Future electricity distribution grids will host a considerable share of variable renewable energy sources and local storage resources. Moreover, they will face new load structures due for example to the growth of the electric vehicle market. These trends raise the need for new paradigms for distribution grids operation, in which Distribution System Operators will increasingly rely on demand side flexibility and households will progressively become prosumers playing an active role on smart grid energy management. However, in present energy management architectures, the lack of coordination among actors limits the capability of the grid to enable the mentioned trends. In this paper we tackle this problem by proposing an architecture that enables households to autonomously exchange energy blocks and flexibility services with neighbors, operators and market actors. The solution is based on a blockchain transactive platform. We focus on a market application, where households can trade energy with their neighbors, aimed to locally balancing renewable energy production. We propose a market mechanism and dynamic transport prices that provide an incentive for households to locally manage energy resources in a way that responds to both prosumer and operator needs. We evaluate the impact of such markets through comprehensive simulations using power flow analysis and realistic load profiles, providing valuable insight for the design of appropriate mechanisms and incentives.

Abstract. A surveillance area is to be monitored using a grid network of heterogeneous sensor nodes. There are two types of nodes; type 0 nodes which perform sensing and relaying of data within a cluster, and type 1 nodes which act as cluster heads or fusion points. A surveillance aircraft visits the area periodically, and gathers information about the activity in the area. During each data gathering cycle, the sensor nodes use multihopping to communicate with their respective cluster heads, while the cluster heads perform data fusion, and transmit the aggregated data directly to the aircraft. We formulate and solve a cost based optimization problem to determine the optimum number of sensor nodes (n0), cluster head nodes (n1) and the battery energy in each type of nodes (E0 and E1 respectively) to ensure at least T data gathering cycles. We observe that the number of cluster heads required, n1, scales approximately as n0 1− k 4 where k is the propagation loss exponent.