Mohamad Ahmadi
Albert-Ludwigs-Universität
Institut für Informatik
Georges-Köhler-Allee 106
D - 79110 Freiburg im Breisgau
Room:
Phone:
Fax:
106-00-003
+49 761 - 203 67419
+49 761 - 203 67412
Email: mahmadi@cs.uni-freiburg.de
I am a PhD candidate at the computer science department of University of Freiburg. I received my M.Sc. in distributed systems engineering from the computer science department of Technical University of Dresden and my B.Sc. in computer engineering in Tehran, Iran.
I am interested in network algorithms and generally in theory of distributed computing.
Teachings
Invited Talks
Broadcasting in Dynamic Radio Networks
2016 1st workshop on Dynamic Graphs in Distributed Computing
(DGDC) in conjunction with DISC conference, Paris, France
Publications
Years: 2019 |
2018 |
2016 |
2015 | show all Conference papers Mohamad Ahmadi, Fabian Kuhn, Shay Kutten, Anisur Rahaman Molla, Gopal PanduranganThe Communication Cost of Information Spreading in Dynamic Networks 2019 39th IEEE Int. Conf. on Distributed Computing Systems (ICDCS), Dallas, USA » show abstract « hide abstract Abstract This paper investigates the message complexity of distributed information spreading in adversarial dynamic net- works. While distributed computations in dynamic networks have been studied intensively over the last years, almost all of the existing work solely focuses on the time complexity of distributed algorithms.
In information spreading, the goal is to spread k tokens of information to every node on an n-node network. We consider the amortized (average) message complexity of spreading a token, assuming that the number of tokens is large. In a static network, this basic problem can be solved using (asymptotically optimal) O(n) amortized messages per token.
Our focus is on token-forwarding algorithms, which do not manipulate tokens in any way other than storing, copying, and forwarding them. We present two sets of results depending on how nodes send messages to their neighbors:
1. Local broadcast: We show a tight lower bound of \tilde{Ω}(n^2) on the number of amortized local broadcasts, which is matched by the naive flooding algorithm. The lower bound holds for randomized algorithms against a strongly adaptive adversary.
2. Unicast: We study the message complexity as a function of the number of dynamic changes in the network. To facilitate this, we introduce adversary-competitive message complexity as a natural complexity measure for analyzing dynamic networks: The adversary pays a unit cost for every topological change and the message cost of an algorithm is determined as the actual number of messages sent minus the total cost of the adversary. Under this model, we give a deterministic algorithm that obtains an optimal amortized message complexity of O(n) if the number of tokens k is sufficiently large. We also present a randomized algorithm that achieves subquadratic amortized message complexity for much smaller k under an oblivious adversary. Journal Papers Mohamad Ahmadi, Abdolhamid Ghodselahi, Fabian Kuhn, Anisur Rahaman MollaThe Cost of Global Broadcast in Dynamic Radio Networks 2019 Theor Comput Sci » show abstract « hide abstract Abstract We study the time complexity of single and multi token broadcast in adversarial dynamic radio networks. Initially, k tokens (which are k pieces of information) are distributed among the n nodes of a network and all the tokens need to be disseminated to all the nodes in the network. We first consider the single-token broadcast problem (i.e., the case k=1). By presenting upper and lower bounds, we show that the time complexity of single-token broadcast depends on the amount of stability and connectivity of the dynamic network topology and on the adaptiveness of the adversary providing the dynamic topology. Then, we give two generic algorithms which allow to transform generalized forms of single-token broadcast algorithms into multi-token broadcast (k-token broadcast) algorithms. Based on these generic algorithms, we obtain k-token broadcast algorithms for a number of different dynamic network settings. For one of the modeling assumptions, our algorithm is complemented by a lower bound which shows that the upper bound is close to optimal. Conference papers Mohamad Ahmadi, Fabian Kuhn, Rotem OshmanDistributed Approximate Maximum Matching in the CONGEST Model 2018 32th Int. Symp. on Distributed Computing (DISC), New Orleans, USA » show abstract « hide abstract Abstract We study distributed algorithms for the maximum matching problem in the CONGEST model, where each message must be bounded in size. We give new deterministic upper bounds, and a new lower bound on the problem.
We begin by giving a distributed algorithm that computes an exact maximum (unweighted) matching in bipartite graphs, in O(n log n) rounds.
Next, we give a distributed algorithm that approximates the fractional weighted maximum matching problem in general graphs. In a graph with maximum degree at most Delta, the algorithm computes a (1-eps)-approximation for the problem in time O(log(Delta W)/eps^2), where W is a bound on the ratio between the largest and the smallest edge weight. Next, we show a slightly improved and generalized version of the deterministic rounding algorithm of Fischer [DISC '17]. Given a fractional weighted maximum matching solution of value f for a given graph G, we show that in time O((log^2(Delta)+log^*n)/eps), the fractional solution can be turned into an integer solution of value at least (1-eps)f for bipartite graphs and (1-\eps).f.(g-1)/g for general graphs, where g is the length of the shortest odd cycle of G. Together with the above fractional maximum matching algorithm, this implies a deterministic algorithm that computes a (1-eps).f.(g-1)/g-approximation for the weighted maximum matching problem in time O(log(Delta W)/eps^2 + (log^2(Delta)+log^* n)/eps).
On the lower-bound front, we show that even for unweighted fractional maximum matching in bipartite graphs, computing an (1 - O(1/sqrt{n}))-approximate solution requires at least Omega(D+sqrt{n}) rounds in CONGEST (ignoring log factors). This lower bound requires the introduction of a new 2-party communication problem, for which we prove a tight lower bound. Conference papers Mohamad Ahmadi, Fabian KuhnMulti-Message Broadcast in Dynamic Radio Networks 2016 12th Int. Symp. on Algorithms and Experiments for Wireless Sensor Networks (ALGOSENSORS), Aarhus, Denmark » show abstract « hide abstract Abstract We continue the recent line of research studying information dissemination problems in adversarial
dynamic radio networks. We give two generic algorithms which allow to transform generalized version
of single-message broadcast algorithms into multi-message broadcast algorithms. Based on these generic
algorithms, we obtain multi-message broadcast algorithms for dynamic radio networks for a number of
different dynamic network settings. For one of the modeling assumptions, our algorithms are complemented
by a lower bound which shows that the upper bound is close to optimal. Conference papers Mohamad Ahmadi, Abdolhamid Ghodselahi, Fabian Kuhn, Anisur Rahaman MollaThe Cost of Global Broadcast in Dynamic Radio Networks 2015 19th Int. Conf. on Principles of Distributed Systems (OPODIS), Rennes, France » show abstract « hide abstract Abstract We study the single-message broadcast problem in dynamic radio
networks. We show that the time complexity of the problem depends on
the amount of stability and connectivity of the dynamic network
topology and on the adaptiveness of the adversary providing the
dynamic topology. More formally, we model communication using the
standard graph-based radio network model. To model the dynamic
network, we use a variant of the synchronous dynamic graph model
introduced in [Kuhn et al., STOC 2010]. For integer parameters
$T\geq 1$ and $k\geq 1$, we call a dynamic graph $T$-interval
$k$-connected if for every interval of $T$ consecutive rounds, there
exists a $k$-vertex-connected stable subgraph. Further, for an
integer parameter $\tau\geq 0$, we say that the adversary providing
the dynamic network is $\tau$-oblivious if for constructing the
graph of some round $t$, the adversary has access to all the
randomness (and states) of the algorithm up to round $t-\tau$.
As our main result, we show that for any $T\geq 1$, any $k\geq 1$,
and any $\tau\geq 1$, for a $\tau$-oblivious adversary, there is a
distributed algorithm to broadcast a single message in time
$O\big(\big(1+\frac{n}{k\cdot \min \set{\tau,T}} \big ) \cdot n \log^3
n \big)$. We further show that even for large interval
$k$-connectivity, efficient broadcast is not possible for the usual
adaptive adversaries. For a $1$-oblivious adversary, we show that
even for any $T\leq (n/k)^{1-\eps}$ (for any constant $\eps > 0$) and for
any $k\geq 1$, global broadcast in $T$-interval $k$-connected
networks requires at least $\Omega(n^2/k^2\log n)$ time. Further,
for a $0$-oblivious adversary, broadcast cannot be solved in
$T$-interval $k$-connected networks as long as $T<n-k$.