6,219 research outputs found
Data Collection and Node Counting by Opportunistic Communication
Ever more powerful mobile devices are nowadays capable of collectively carrying out reasonably demanding computational tasks without offloading the processing to an edge server or a distant cloud-computing service. In this work, we explore such distributed computing and study how it is affected by the mobility as well as the number of nodes that collaborate. We choose distributed counting of a number of nodes in an enclosed area as application. Such application is useful for estimating attendance at events and measuring occupancy for facility management, as needed for monitoring of crowdedness with respect to safety and evacuation, climate control and comfort. For this application, we are interested in determining the time until all nodes know the correct number of nodes in the space where they reside. Our study shows the effect of mobility on the distributed process. We find that the process of collecting data opportunistically from a closed set of nodes is well described by empirical laws that we derive. We discuss the results and suggest further work needed to understand opportunistic computation and to develop it as a new model of computation among collectives of mobile nodes.Peer reviewe
Let the Tree Bloom: Scalable Opportunistic Routing with ORPL
Routing in battery-operated wireless networks is challenging, posing a tradeoff between energy and latency. Previous work has shown that opportunistic routing can achieve low-latency data collection in duty-cycled networks. However, applications are now considered where nodes are not only periodic data sources, but rather addressable end points generating traffic with arbitrary patterns.
We present ORPL, an opportunistic routing protocol that supports any-to-any, on-demand traffic. ORPL builds upon RPL, the standard protocol for low-power IPv6 networks. By combining RPL's tree-like topology with opportunistic routing, ORPL forwards data to any destination based on the mere knowledge of the nodes' sub-tree. We use bitmaps and Bloom filters to represent and propagate this information in a space-efficient way, making ORPL scale to large networks of addressable nodes. Our results in a 135-node testbed show that ORPL outperforms a number of state-of-the-art solutions including RPL and CTP, conciliating a sub-second latency and a sub-percent duty cycle. ORPL also increases robustness and scalability, addressing the whole network reliably through a 64-byte Bloom filter, where RPL needs kilobytes of routing tables for the same task
A Faster Counting Protocol for Anonymous Dynamic Networks
We study the problem of counting the number of nodes in a slotted-time
communication network, under the challenging assumption that nodes do not have
identifiers and the network topology changes frequently. That is, for each time
slot links among nodes can change arbitrarily provided that the network is
always connected. Tolerating dynamic topologies is crucial in face of mobility
and unreliable communication whereas, even if identifiers are available, it
might be convenient to ignore them in massive networks with changing topology.
Counting is a fundamental task in distributed computing since knowing the size
of the system often facilitates the design of solutions for more complex
problems. Currently, the best upper bound proved on the running time to compute
the exact network size is double-exponential. However, only linear complexity
lower bounds are known, leaving open the question of whether efficient Counting
protocols for Anonymous Dynamic Networks exist or not. In this paper we make a
significant step towards answering this question by presenting a distributed
Counting protocol for Anonymous Dynamic Networks which has exponential time
complexity. Our algorithm ensures that eventually every node knows the exact
size of the system and stops executing the algorithm. Previous Counting
protocols have either double-exponential time complexity, or they are
exponential but do not terminate, or terminate but do not provide running-time
guarantees, or guarantee only an exponential upper bound on the network size.
Other protocols are heuristic and do not guarantee the correct count
Social-Aware Forwarding Improves Routing Performance in Pocket Switched Networks
Several social-aware forwarding strategies have been recently introduced in
opportunistic networks, and proved effective in considerably in- creasing
routing performance through extensive simulation studies based on real-world
data. However, this performance improvement comes at the expense of storing a
considerable amount of state information (e.g, history of past encounters) at
the nodes. Hence, whether the benefits on routing performance comes directly
from the social-aware forwarding mechanism, or indirectly by the fact state
information is exploited is not clear. Thus, the question of whether
social-aware forwarding by itself is effective in improving opportunistic
network routing performance remained unaddressed so far. In this paper, we give
a first, positive answer to the above question, by investigating the expected
message delivery time as the size of the net- work grows larger
Emulating opportunistic networks with KauNet Triggers
In opportunistic networks the availability of an end-to-end path is no longer required. Instead opportunistic networks may take advantage of temporary connectivity opportunities.
Opportunistic networks present a demanding environment for network emulation as the traditional emulation setup, where application/transport endpoints only send and receive packets from the network following a black box approach,
is no longer applicable. Opportunistic networking protocols
and applications additionally need to react to the dynamics of the underlying network beyond what is conveyed through the exchange of packets.
In order to support IP-level emulation evaluations of applications and protocols that react to lower layer events, we have proposed the use of emulation triggers. Emulation triggers can emulate arbitrary cross-layer feedback and can be synchronized with other emulation effects. After introducing the design and implementation of
triggers in the KauNet emulator, we describe the integration of triggers with the DTN2 reference implementation and illustrate how the functionality can be used to emulate a classical DTN data-mule scenario
Time-Varying Graphs and Dynamic Networks
The past few years have seen intensive research efforts carried out in some
apparently unrelated areas of dynamic systems -- delay-tolerant networks,
opportunistic-mobility networks, social networks -- obtaining closely related
insights. Indeed, the concepts discovered in these investigations can be viewed
as parts of the same conceptual universe; and the formal models proposed so far
to express some specific concepts are components of a larger formal description
of this universe. The main contribution of this paper is to integrate the vast
collection of concepts, formalisms, and results found in the literature into a
unified framework, which we call TVG (for time-varying graphs). Using this
framework, it is possible to express directly in the same formalism not only
the concepts common to all those different areas, but also those specific to
each. Based on this definitional work, employing both existing results and
original observations, we present a hierarchical classification of TVGs; each
class corresponds to a significant property examined in the distributed
computing literature. We then examine how TVGs can be used to study the
evolution of network properties, and propose different techniques, depending on
whether the indicators for these properties are a-temporal (as in the majority
of existing studies) or temporal. Finally, we briefly discuss the introduction
of randomness in TVGs.Comment: A short version appeared in ADHOC-NOW'11. This version is to be
published in Internation Journal of Parallel, Emergent and Distributed
System
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