Migration and replication of virtual network functions (VNFs) are well-known mechanisms to face dynamic resource requests in Internet Service Provider (ISP) edge networks. They are not only used to reallocate resources in carrier networks, but in case of excessive traffic churns also to offloading VNFs to third party cloud providers. We propose to study how traffic forecasting can help to reduce the number of required migrations and replications when the traffic dynamically changes in the network. We analyze and compare three scenarios for the VNF migrations and replications based on: (i) the current observed traffic demands only, (ii) specific maximum traffic demand value observed in the past, or (iii) predictive traffic values. For the prediction of traffic demand values, we use an LSTM model which is proven to be one of the most accurate methods in time series forecasting problems. Based the traffic prediction model, we then use a Mixed-Integer Linear Programming (MILP) model as well as a greedy algorithm to solve this optimization problem that considers migrations and replications of VNFs. The results show that LSTM-based traffic prediction can reduce the number of migrations up to 45\% when there is enough available resources to allocate replicas, while less cloud-based offloading is required compared to overprovisioning.

Parallelism has become one of the key architectural features in 40-/100-/400-Gb Ethernet multi lane distribution (MLD) standards. The MLD packetizes and distributes traffic adaptively over parallel lanes and maps them to parallel network interfaces for wide area transmission, typically over optical networks. As such, the MLD creates not only new network topology abstractions but also enables modular implementations of various new features to improve the system performance. In this paper, we study the performance of the parallelized Ethernet in combination with erasure coding and more specifically random linear network coding (RLNC). We present a novel theoretical modeling framework, including the derivation of upper and lower bounds of differential delay and the resulting receiver queue size-a critical performance measure in the high-speed Ethernet. The results show benefits of a combined usage of parallelism and RLNC: with a proper set of design parameters, the differential delay and the receiver buffer size can be reduced significantly, while cross-layer design and path computation greatly simplified.

Scrambling or information randomization has been effectively used in various applications to prevent the information falling into the hands of rogue attackers. In this paper, we use the idea of spectrum scrambling to proactively randomize the spectrum across multiple fiber cores to improve connections' security, while at the same time effectively defragmenting the spectrum to improve connections' blocking performance. To this end, we propose a scheme called random spectrum defragmentation (RSD), and model the occupancy pattern of a multi-core fiber link using a multi-class continuous-time Markov chain (CTMC) under the two different spectrum allocation methods, first-fit and random-fit. As the efforts have been on preventing unauthorized access to optical channels, we show that scrambling can be effectively used to help dealing with the physical layer attacks. At the same time, numerical results show that also the blocking can be improved for a particular so-called randomization process (RP) arrival rate, and lower connection reconfiguration time.

Data randomization or scrambling has been effectively used in various applications to improve the data security. In this paper, we use the idea of data randomization to proactively randomize the spectrum (re)allocation to improve connections' security. As it is well-known that random (re)allocation fragments the spectrum and thus increases blocking in elastic optical networks, we analyze the tradeoff between system performance and security. To this end, in addition to spectrum randomization, we utilize an on-demand defragmentation scheme every time a request is blocked due to the spectrum fragmentation. We model the occupancy pattern of an elastic optical link (EOL) using a multi-class continuous-time Markov chain (CTMC) under the random-fit spectrum allocation method. Numerical results show that although both the blocking and security can be improved for a particular so-called randomization process (RP) arrival rate, while with the increase in RP arrival rate the connections' security improves at the cost of the increase in overall blocking.

Recently, cellular networks have witnessed major developments pertaining to user mobility, rich multimedia service offering and a melange of network access options including 3G/4G, WiFi, WiMAX, etc. As a result, sessions are expected to last longer and users are more likely to roam between access technologies and to other networks. As architectural design is advancing in all-IP cellular systems such as the Long Term Evolution (LTE), the question we propose to address is whether the established results on handoff and roaming statistics used in cellular theory still apply. To this end, we revisit the theory for handoff statistics and take up the challenge on extending the current model under general assumptions for session distributions, user mobility, network coverage and access technology. We show that the derived model yields estimates of handoff frequency and roaming statistics which cannot be obtained otherwise. The key strength of the proposed analysis is offering closed form results, which are easy to use and can lead to more accurate conclusions about the signaling load and the observed QoS, as a direct function of handoff statistics.

The mean number of handoffs is a fundamental performance measure in any mobile system, as it directly relates to the signaling load in the network as well as to the delivered QoS. As the mobile services are evolving from simple cellular voice calls towards media and data sessions, and as cellular providers are reinventing their businesses by incorporating third party services, the handoff rate will even play a more pivotal role. This is because future sessions are expected to last longer than voice calls and users are more likely to roam into other networks. Existing results provide an estimate of the mean number of handoffs in networks composed of an infinite number of access gateways and hence consider neither the topological arrangement of the gateways nor the mobility patterns between them. In this paper, we obtain a closed form solution for the mean number of handoffs under generic assumptions of two- dimensional Markovian mobility patterns, spatial arrangement of the access gateways, as well as generic session times and gateway residence times. Our solution unveils a new insight into mobility foundations as it shows that the consideration of the mobility pattern and the access gateways' layout simply transforms the known equation for the mean number of handoffs of an infinite network size from scalar to vector representation. We demonstrate that the mean number of handoffs is a non-linear function of the gateway spatial arrangement and user mobility.

The backhaul network, which connects base stations to the radio network controllers, poses a major challenge in cellular networks today due to the expensive maintenance, operation and poor scalability in response to traffic dynamicity. The majority of the present backhaul networks is composed of either leased lines, i.e., T1/E1 and/or microwave links. Recently, wireless mesh networks have been proposed as a possible backhaul transport media, not only for their significant cost savings but also for their scale, flexibility and resilience. At the same time, however, wireless mesh backhauls pose many technical challenges including timing synchronization for GSM networks, bandwidth reservation techniques, dynamic bandwidth control, and billing. To address some of these challenges, we propose the first ever billing architecture for wireless mesh networks and analyze its performance and scalability in response to a novel, threshold based bandwidth management algorithm. Using analysis based on a simple Markov process, we evaluate a highly unstable reservation mechanism and establish the corresponding upper bounds on the billing signaling performance over mesh backhauls. The analysis and simulation results show that our billing scheme scales well even for poor implementations of bandwidth reservations.

In mobile communication systems of the 3/sup rd/ and 4/sup th/ generation the mobile users are expected to demand the same quality of service (QoS) available to fixed users. To investigate the performance of predictive schemes a new mobility model is derived that simulates human behavior in realistic environments. This paper also presents a new adaptive scheme for micro-cellular environments that combines stochastic information with topological information about the cell region to predict the next cell to be visited by the subscriber. The results show that the presented algorithm provides a high prediction accuracy in realistic environments.