Toward manageable middleboxes in software‐defined networking

Software‐defined networking (SDN) acts as a centralized management unit, especially in a network with devices that operate under the transport layer of the OSI model. However, when a network with layer 7 middleboxes (MBs) is considered, current SDNs exhibit limitations. As such, to achieve a real‐centralized management unit, a new architecture is required that decouples the data and control planes of all network devices. In this report, we propose such a complementary architecture to the current SDN in which SDN‐enabled MBs are included along with contemporary SDN‐enabled switches. The management unit of this architecture improves network performance and reduces routing cost by considering the status of the MBs during flow forwarding. This unit consists of the following two parts: an SDN controller (SDNC) and a middlebox controller (MBC). The latter selects the best MBs for each flow and the former determines the best path according to its routing algorithm and provides information via the MBC. The results show that the proposed architecture improved performance because the utilization of all network devices including MBs is manageable.     

KDB: a fast update and high speed packet classifier in SDN

The Journal of Supercomputing - Packet classification is a fundamental function to support several services of software defined networking (SDN). Increasing complexity of the flow tables in SDN...     

Fault-Tolerant and 3-Dimensional Distributed Topology Control Algorithms in Wireless Multi-hop Networks

The topology of a multi-hop wireless network can be controlled by varying the transmission power at each node. The life-time of such networks depends on battery power at each node. This paper presents a distributed fault-tolerant topology control algorithm for minimum energy consumption in multi-hop wireless networks. This algorithm is an extension of cone-based topology control algorithm [19, 12]. The main advantage of this algorithm is that each node decides on its power based on local information about the relative angle of its neighbors and as a result of these local decisions, a fault-tolerant connected network is formed on the nodes. It is done by preserving the connectivity of a network upon failing of, at most, k nodes (k is a constant) and simultaneously minimize the transmission power at each node to some extent. In addition, simulations are studied to support the effectiveness of this algorithm. Finally, it is shown how to extend this algorithm to 3-dimensions. An extended abstract version of this paper appeared in the 11th IEEE International Conference on Computer Communications and Networks(ICCCN02). Mohsen Bahramgiri born in 1979, recieved the Bachelor's degree in Mathematical Sciences from Sharif University of Technology, Tehran, Iran in 2000. He is now a PhD candidate in Mathematics Department at Massachusetts Institute of Technology. His research interests include Symplectic Hodge Theory on Higher dimentional Geometry, Kahler Geometry, Mathematical Physics and Geometric Analysis on one hand, and algorithmic Graph Theory and Combinatorics on the other hand. MohammadTaghi Hajiaghayi received the Bachelor's degree in computer engineering from Sharif University of Technology in 2000. He received the Master's degree in Computer Science from the University of Waterloo in 2001. Since 2001, he is a Ph.D. candidate in Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. During his Ph.D. studies, he also worked at the IBM T.J. Watson Research Center (Department of Mathematical Sciences) and at the Microsoft Research (Theory group). His research interests are algorithmic graph theory, combinatorial optimizations, distributed and mobile computing, computational geometry and embeddings, game theory and combinatorial auctions, and random structures and algorithms. Vahab S. Mirrokni received the Bachelor's degree in computer engineering from Sharif University of Technology, Tehran, Iran in 2001. Since 2001, he is a Ph.D. candidate in Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. During his Ph.D. studies, he also worked at the Bell-Laboratories (Networking Center and Department of Fundamental Mathematics). His research interests include approximation algorithms, combinatorial optimization, computational game theory, mobile computing, network mannagement, and algorithmic graph theory.     

Robust network coding against path failures

In this study, an approach for robust network coding is introduced for multicast in a directed acyclic network in the presence of network edge failures. The proposed designs aim at combating the resulting path failures, which result in interestingly scalable solutions. A robust network coding scheme (RNC1) is proposed that, devising a rate-path diversity trade-off for the receivers, attains the post-failure capacity of the network with high probability. The scheme is receiver based and can also be applied for correcting random erasures. Next, a rate-guaranteed robust network coding scheme (RNC2) is proposed. The code guarantees the maximum rate for a predetermined number of path failures. The scheme, of course, attains the refined Singleton bound for the edge failure model. A path failure may not necessarily reduce the network capacity, as the remaining intact edges within the network may still facilitate backup paths from the source to the sinks. We introduce RNC3 to employ such backup paths in addition to the original paths and guarantee multicast at a certain rate in the presence of all edge/path failure patterns that do not reduce the capacity below this rate. All the three proposed schemes for multicast are robust to a number of edge failures that may, in general, exceed the refined Singleton bound. Our analyses indicate that the design complexities and the required field sizes grow as a function of the number of network paths, as opposed to the number of network edges because of prior schemes.     

Joint synchronization and parameter estimation in OFDM signaling

Challenges in cognitive radio and tactical communications include recognizing anonymously received signals and estimating parameters in a blind or semiblind manner. In this paper, we examine this issue for orthogonal frequency division multiplexing (OFDM) signaling. There are several parameters in OFDM signaling, and the blind receiver must extract and consider the synchronization issue. We assume that the blind receiver is aware of modulation type, OFDM, and not aware of chip duration and the length of cyclic prefix. First, we present new criteria based on kurtosis to estimate these parameters and compare their performance at different levels of additive white Gaussian noise with methods based on correlation, kurtosis, maximum likelihood, and matched filter. Then, we perform synchronization and estimate the start time based on these criteria and several new criteria in two steps: fine and coarse synchronization. Finally, in a more practical setup, we present the idea of jointly estimating the mentioned parameters and the signal start time as coarse synchronization. We compare different criteria and show that one of the proposed criteria has the highest efficiency.