We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

In the Hamadryas baboon, males are substantially larger than females. A troop of baboons is subdivided into a number of ‘one-male groups’, consisting of one adult male and one or more females with their young. The male prevents any of ‘his’ females from moving too far from him. Kummer (1971) performed the following experiment. Two males, A and B, previously unknown to each other, were placed in a large enclosure. Male A was free to move about the enclosure, but male B was shut in a small cage, from which he could observe A but not interfere. A female, unknown to both males, was then placed in the enclosure. Within 20 minutes male A had persuaded the female to accept his ownership. Male B was then released into the open enclosure. Instead of challenging male A , B avoided any contact, accepting A’s ownership.

Evolution and the Theory of Games

Information flow in a telecommunication network is accomplished through the interaction of mechanisms at various design layers with the end goal of supporting the information exchange needs of the applications. In wireless networks in particular, the different layers interact in a nontrivial manner in order to support information transfer. In this text we will present abstract models that capture the cross-layer interaction from the physical to transport layer in wireless network architectures including cellular, ad-hoc and sensor networks as well as hybrid wireless-wireline. The model allows for arbitrary network topologies as well as traffic forwarding modes, including datagrams and virtual circuits. Furthermore the time varying nature of a wireless network, due either to fading channels or to changing connectivity due to mobility, is adequately captured in our model to allow for state dependent network control policies. Quantitative performance measures that capture the quality of service requirements in these systems depending on the supported applications are discussed, including throughput maximization, energy consumption minimization, rate utility function maximization as well as general performance functionals. Cross-layer control algorithms with optimal or suboptimal performance with respect to the above measures are presented and analyzed. A detailed exposition of the related analysis and design techniques is provided.

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Resource Allocation and Cross Layer Control in Wireless Networks

We present a simple dictionary with worst case constant lookup time, equaling the theoretical performance of the classic dynamic perfect hashing scheme of Dietzfelbinger et al. [SIAM J. Comput. 23 (4) (1994) 738-761]. The space usage is similar to that of binary search trees. Besides being conceptually much simpler than previous dynamic dictionaries with worst case constant lookup time, our data structure is interesting in that it does not use perfect hashing, but rather a variant of open addressing where keys can be moved back in their probe sequences. An implementation inspired by our algorithm, but using weaker hash functions, is found to be quite practical. It is competitive with the best known dictionaries having an average case (but no nontrivial worst case) guarantee on lookup time.

Cuckoo hashing

In this paper, we consider the question of determining whether a function f has property P or is e-far from any function with property P. A property testing algorithm is given a sample of the value of f on instances drawn according to some distribution. In some cases, it is also allowed to query f on instances of its choice. We study this question for different properties and establish some connections to problems in learning theory and approximation.In particular, we focus our attention on testing graph properties. Given access to a graph G in the form of being able to query whether an edge exists or not between a pair of vertices, we devise algorithms to test whether the underlying graph has properties such as being bipartite, k-Colorable, or having a p-Clique (clique of density p with respect to the vertex set). Our graph property testing algorithms are probabilistic and make assertions that are correct with high probability, while making a number of queries that is independent of the size of the graph. Moreover, the property testing algorithms can be used to efficiently (i.e., in time linear in the number of vertices) construct partitions of the graph that correspond to the property being tested, if it holds for the input graph.

Property Testing and its connection to Learning and Approximation

Evolutionary equilibrium in Bayesian routing games: Specialization and niche formation

The bin packing problem is defined as follows: given a set of n items with sizes 00, we present an algorithm A"@e that has sampling access to the input instance and outputs a value k such that C"o"p"t@?k@?(1+@e)@?C"o"p"t+1, where C"o"p"t is the cost of an optimal solution. It is clear that uniform sampling by itself will not allow a sublinear-time algorithm in this setting; a small number of items might constitute most of the total weight and uniform samples will not hit them. In this work we use weighted samples, where item i is sampled with probability proportional to its weight: that is, with probability w"i/@?"iw"i. In the presence of weighted samples, the approximation algorithm runs in O@?(n@?poly(1/@e))+g(1/@e) time, where g(x) is an exponential function of x. When both weighted sampling and uniform sampling are allowed, O@?(n^1^/^3@?poly(1/@e))+g(1/@e) time suffices. In addition to an approximate value to C"o"p"t, our algorithm can also output a constant-size ''template'' of a packing that can later be used to find a near-optimal packing in linear time.

A sublinear-time approximation scheme for bin packing

Population protocols are a distributed model focused on simplicity and robustness. A system of $n$ identical nodes must perform a global task like electing a unique leader or determining the majority opinion when each node has one of two opinions. Nodes communicate in pairwise interactions. Communication partners cannot be chosen but are assigned randomly. Quality is measured in two ways: the number of interactions and the number of states per node. 
Under strong stability requirements, when the protocol may not fail with even negligible probability, the best protocol for leader election requires $O(n \cdot {(\log n)}^2)$ interactions and $O(\log\log n)$ states [Gasieniec and Stachowiak; SODA'18]. The best protocol for majority requires $O(n \cdot {(\log n)}^2)$ interactions and $O(\log n)$ states [Alistarh, Aspnes, and Gelashvili; SODA'18]. Both bounds are known to be space-optimal for protocols with subquadratic many interactions. 
We present protocols which allow for a trade-off between space and time. Compared to another trade-off result [Alistarh, Gelashvili, Vojnovic; PODC'15], we improve the number of interactions by almost a linear factor. Compared to the state of the art, we match their bounds and, at a moderate cost in terms of states, improve upon the number of interactions. Our results extend to a slightly weaker "stability" notion known as convergence.

Majority & Stabilization in Population Protocols.

In this paper we study the problem of scheduling real-time requests in distributed data servers. We assume the time to be divided into time steps of equal length called rounds. During every round a set of requests arrives at the system, and every resource is able to fulfill one request per round. Every request specifies two (distinct) resources and requires to get access to one of them. Furthermore, every request has a deadline of d, i.e. a request that arrives in round t has to be fulfilled during round t + d 1 at the latest. The number of requests which arrive during some round and the two alternative resources of every request are selected by an adversary. The goal is to maximize the number of requests that are fulfilled before their deadlines expire. We examine the scheduling problem in an online setting, i.e. new requests continuously arrive at the system, and we have to determine online an assignment of the requests to the resources in such a way that every resource has to fulfill at most one request per round. We study both global (i.e. centralized) and local (i.e. distributed) scheduling strategies. In order to measure the performance of our scheduling strategies we apply competitive analyses. Previously, no non-trivial bounds have been known for the competitive ratio of scheduling strategies in our model. We present (partly matching) upper and lower bounds for several simple scheduling strategies.

/pdf/simple-competitive-request-scheduling-strategies-56fzca2z5y.pdf

Simple competitive request scheduling strategies

The study of balls-into-bins games or occupancy problems has a long history since these processes can be used to translate realistic problems into mathematical ones in a natural way. In general, the goal of a balls-into-bins game is to allocate a set of independent objects (tasks, jobs, balls) to a set of resources (servers, bins, urns) and, thereby, to minimize the maximum load. In this paper we show two results. First, we analyse the maximum load for the chains-into-bins problem where we have n bins and the balls are connected in n/l chains of length l. In this process, the balls of one chain have to be allocated to l consecutive bins. We allow each chain d i.u.r.\ bin choices. The chain is allocated using the rule that the maximum load of any bin receiving a ball of that chain is minimized. We show that, for d ≥ 2, the maximum load is (ln ln (n/l))/ln d +O(1) with probability 1-O(1/lnln(n/l)). This shows that the maximum load is decreasing with increasing chain length. Secondly, we analyse for which number of random choices d and which number of balls m, the maximum load of an off-line assignment can be upper bounded by one. This holds, for example, for m<0.97677 n and d=4.

/pdf/balanced-allocations-balls-into-bins-revisited-and-chains-3bdvtzv12d.pdf

Petra Berenbrink

Papers

Evolutionary equilibrium in Bayesian routing games: Specialization and niche formation

A sublinear-time approximation scheme for bin packing

Majority & Stabilization in Population Protocols.

Simple competitive request scheduling strategies

Balanced allocations: balls-into-bins revisited and chains-into-bins