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The virtualization and softwarization of modern computer networks enables the definition and fast deployment of novel network services called service chains: sequences of virtualized network functions (e.g., firewalls, caches, traffic optimizers) through which traffic is routed between source and destination. This paper attends to the problem of admitting and embedding a maximum number of service chains, i.e., a maximum number of source-destination pairs which are routed via a sequence of to-be-allocated, capacitated network functions. We consider an Online variant of this maximum Service Chain Embedding Problem, short OSCEP, where requests arrive over time, in a worst-case manner. Our main contribution is a deterministic O(log )-competitive online algorithm, under the assumption that capacities are at least logarithmic in . We show that this is asymptotically optimal within the class of deterministic and randomized online algorithms. We also explore lower bounds for offline approximation algorithms, and prove that the offline problem is APX-hard for unit capacities and small ≥ 3, and even Poly-APX-hard in general, when there is no bound on . These approximation lower bounds may be of independent interest, as they also extend to other problems such as Virtual Circuit Routing. Finally, we present an exact algorithm based on 0-1 programming, implying that the general offline SCEP is in NP and by the above hardness results it is NP-complete for constant .

Multiple hop routing in mobile ad hoc networks can minimize energy consumption and increase data throughput. Yet, the problem of radio interferences remains. However if the routes are restricted to a basic network based on local neighborhoods, these interferences can be reduced such that standard routing algorithms can be applied. We compare different network topologies for these basic networks with respect to degree, spanner-properties, radio interferences, energy, and congestion, i.e. the Yao-graph (aka. Θ-graph) and some also known related models, which will be called the SymmY-graph (aka. YS-graph), the SparsY-graph (aka.YY-graph) and the BoundY-graph. Further, we present a promising network topology called the HL-graph (based on Hierarchical Layers). Further, we compare the ability of these topologies to handle dynamic changes of the network when radio stations appear and disappear. For this we measure the number of involved radio stations and present distributed algorithms for repairing the network structure. MotivationOur research aims at the implementation of a mobile ad hoc network based on distributed robust communication protocols. Besides the traditional use of omni-directional transmitters, we want to investigate the effect of space multiplexing techniques and variable transmission powers on the efficiency and capacity of ad hoc networks. Therefore our radios can send and receive radio signals independently in k sectors of angle θ using one frequency. Furthermore, our radio stations can regulate its transmission power for each transmitted signal. To show that this approach is also suitable in practical situations, we are currently developing a communication module for the mini robot Khepera [11,8] that can transmit and receive in eight sectors using infrared light with variable transmission distances up to one meter, see Fig. 1. A colony of Khepera robots will be equipped with

The virtualization and softwarization of modern computer networks introduces interesting new opportunities for a more flexible placement of network functions and middleboxes (firewalls, proxies, traffic optimizers, virtual switches, etc.). This paper studies approximation algorithms for the incremental deployment of a minimum number of middleboxes at optimal locations, such that capacity constraints at the middleboxes and length constraints on the communication routes are respected. Our main contribution is a new, purely combinatorial and rigorous proof for the submodularity of the function maximizing the number of communication requests that can be served by a given set of middleboxes. Our proof allows us to devise a deterministic approximation algorithm which uses an augmenting path approach to compute the submodular function. This algorithm does not require any changes to the locations of existing middleboxes or the preemption of previously served communication pairs when additional middleboxes are deployed, previously accepted communication pairs just can be handed over to another middlebox. It is hence particularly attractive for incremental deployments. We prove that the achieved polynomialtime approximation bound is optimal, unless P = NP . This paper also initiates the study of a weighted problem variant, in which entire groups of nodes need to communicate via a middlebox (e.g., a multiplexer or a shared object), possibly at different rates. We present an LP relaxation and randomized rounding algorithm for this problem, leveraging an interesting connection to scheduling.

Abstract. We present an external memory algorithm to compute a well-separated pair decomposition (WSPD) of a given point set P in