VNF placement optimization at the edge and cloud

Network Function Virtualization (NFV) has revolutionized the way network services are offered to end users. Individual network functions are decoupled from expensive and dedicated middleboxes and are now provided as software-based virtualized entities called Virtualized Network Functions (VNFs). NFV is often complemented with the Cloud Computing paradigm to provide networking functions t

On minimizing the maximum sensor movement for barrier coverage of a line segment

We consider n mobile sensors located on a line containing a barrier represented by a finite line segment. Sensors form a wireless sensor network and are able to move within the line. An intruder traversing the barrier can be detected only when it is within the sensing range of at least one sensor. The sensor network establishes barrier coverage of the segment if no intruder can penetrate the barrier from any direction in the plane without being detected. Starting from arbitrary initial positions of sensors on the line we are interested in finding final positions of sensors that establish barrier coverage and minimize the maximum distance traversed by any sensor. We distinguish several variants of the problem, based on (a) whether or not the sensors have identical ranges, (b) whether or not complete coverage is possible and (c) in the case when complete coverage is impossible, whether or not the maximal coverage is required to be contiguous. For the case of n sensors with identical range, when complete coverage is impossible, we give linear time optimal algorithms that achieve maximal coverage, both for the contiguous and non-contiguous case. When complete coverage is possible, we give an O(n 2) algorithm for an optimal solution, a linear time approximation scheme with approximation factor 2, and a (1∈+∈ε) PTAS. When the sensors have unequal ranges we show that a variation of the problem is NP-complete and identify some instances which can be solved with our algorithms for sensors with unequal ranges

Optimal admission and routing at a simple data network node

Summary form only given, as follows. A stream of messages reaches the buffer of a node in a communication network, according to a Poisson distribution with parameter λ. The messages are then to be routed over two channels with different propagation times that are exponentially distributed with parameters μ1 and μ2, where μ1 is larger than μ2. Two controls are to be applied at the node. The first control concerns the admission of a message into the buffer, and the second control is responsible for routing the buffered messages over the two channels. The author determines the optimal policy which minimizes an expected cost involving the weighted sum of a penalty for not admitting a message into the buffer and a penalty for the delay experienced by the messages already stored in the buffer

Optimal Control for Network Coding Broadcast

Random linear network coding (RLNC) has been shown to efficiently improve the network performance in terms of reducing transmission delays and increasing the throughput in broadcast and multicast communications. However, it can result in increased storage and computational complexity at the receivers end. In our previous work we considered the broadcast transmission of large file to N receivers. We showed that the storage and complexity requirements at the receivers end can be greatly reduced when segmenting the file into smaller blocks and applying RLNC to these blocks. To that purpose, we proposed a packet scheduling policy, namely the Least Received. In this work we will prove the optimality of our previously proposed policy, in terms of file transfer completion time, when N = 2. We will model our system as a Markov Decision Process and prove the optimality of the policy using Dynamic Programming. Our intuition points that the Least Received policy may be optimal regardless of the number of receivers. Towards that end, we will provide experimental results that agree with this intuition

OPTIMAL CONTROL OF ARRIVALS AT A BLOCKING NODE.

Two communication traffic streams with Poisson statistics arrive at a network node. These are to be transmitted across a channel with a total bandwidth capacity of C frequency slots. Messages not accepted at the node are assumed to be lost. Under the assumption of exponential service time distributions, the authors study the problem of dynamic allocation of available channel bandwidth among the two traffic types to minimize a weighted sum of blocking probabilities. Modeling the system as a two-dimensional Markov chain, they show by an application of dynamic programming principles that the optimal policy is characterized by a set of two switching curves

Performance Evaluation of a New Fairness Control Scheme for Ring Networks with Spatial Reuse

We consider a ring in which simultaneous transmission of messages by different stations is allowed, a property referred to as spatial reuse. A ring network with spatial reuse can achieve a network level throughput much higher than the channel rate. A widely used scheme to achieve spatial reuse is Buffer Insertion Ring (BIR). However, because non-preemptive priority is given to the ring traffic, BIR scheme can lead to fairness problems in distributing the ring bandwidth among distinct nodes. In this paper, we propose a novel approach that provides fair access to all nodes and features low complexity. Within each node, the proposed approach allocates a separate queue for every upstream node. Each queue receives its fair share of the ring bandwidth based on an assigned weight value. Performance of the proposed scheme in terms of fairness and average packet delay has been evaluated through both simulations and analysis. The results show that the new scheme called Source-Based Queuing (SBQ) can provide fairness with less end-to-end delay compare to the BIR scheme