Over the years, challenged networks have evolved from niche solution for extremely hostile scenarios (such as disaster relief or connectivity provision in rural and remote areas) to important component of everyday networks. In their second life, challenged networks have entered mobile cloud/mobile edge computing, IoT, mobile data offloading, and SDN. It is exactly these new directions of challenged networking that are the focus of this 2016 edition of CHANTS. While keeping an eye on the future, we also wanted to tackle a years-old affliction: how to move from theory to practice when dealing with challenged networks. For this reason, we also have a lineup spanning DTN software and testbeds that will speed up the jump from the research lab to marketable products.
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Opportunistic content dissemination performance in dense network segments
Many of the existing opportunistic networking systems have been designed assuming a small number links per node and have trouble scaling to large numbers of potential concurrent communication partners. In the real world we often find wireless local area ...
Mobile triage management in disaster area networks using decentralized replication
In large-scale disaster scenarios, efficient triage management is a major challenge for emergency services. Rescue forces traditionally respond to such incidents with a paper-based triage system, but technical solutions can potentially achieve improved ...
HINT: from network characterization to opportunistic applications
The increasing trend on wireless-connected devices makes opportunistic networking a promising alternative to existing infrastructure-based networks. However, these networks offer no guarantees about connection availability or network topology. The ...
SCTPCL: an SCTP convergence layer protocol for DTN
The Stream Control Transmission Protocol (SCTP) offers several distinct features which can be leveraged for Disruption or Delay Tolerant Networking (DTN). SCTP is able to handle an arbitrary number of independent streams in one connection---termed an ...
(Not so) intuitive results from a smart agriculture low-power wireless mesh deployment
A 21-node low-power wireless mesh network is deployed in a peach orchard. The network serves as a frost event prediction system. On top of sensor values, devices also report network statistics. In 3 months of operations, the network has produced over 4 ...
Opportunistic iot for monitoring of grazing cattle: demo
Precision livestock farming and other agricultural applications are considered to have great potential to utilise the many benefits of IoT technology. It is however important to maintain low cost and energy consumption to make it feasible in a very ...
SierraNet: monitoring the snowpack in the Sierra Nevada: demo
Next-generation hydrologic science and monitoring requires real-time, spatially distributed measurements of key variables including: soil moisture, air/soil temperature, snow depth, and air relative humidity. The SierraNet project provides these ...
Using the HINT network emulator to develop opportunistic applications: demo
In this work, we show how to use HINT, a real-time event-driven network emulator, to support the development process of opportunistic applications. In this demo, we use this emulator in conjunction with an example Android chat application to demonstrate ...
Here&now: data-centric local social interactions through opportunistic networks: demo
Many of today's popular online social networks are disconnected from their users' immediate social and physical context, which makes them poorly suited for supporting transient, on-purpose social communities of co-located users. We introduce the idea of ...
Streaming content from a vehicular cloud
Network densification via small cells is considered as a key step to cope with the data tsunami. Caching data at small cells or even user devices is also considered as a promising way to alleviate the backhaul congestion this densification might cause. ...
Filling the gaps: on the completion of sparse call detail records for mobility analysis
Call Detail Records (CDRs) have been widely used in the last decades for studying different aspects of human mobility. The accuracy of CDRs strongly depends on the user-network interaction frequency: hence, the temporal and spatial sparsity that ...
Soft cache hits and the impact of alternative content recommendations on mobile edge caching
Caching popular content at the edge of future mobile networks has been widely considered in order to alleviate the impact of the data tsunami on both the access and backhaul networks. A number of interesting techniques have been proposed, including ...
Performance implications for IoT over information centric networks
Information centric networking (ICN) is a proposal for a future internetworking architecture that is more efficient and scalable. While several ICN architectures have been evaluated for networks carrying web and video traffic, the benefits and ...
MobCCN: a CCN-compliant protocol for data collection with opportunistic contacts in IoT environments
In IoT environments, a significant fraction of services can be expected to be relevant and contextualised to the physical area where data is generated. This is due to the typical strong bond between IoT devices and the physical environment where they ...
Beacon trains: blazing a trail through dense BLE environments
Bluetooth Low Energy (BLE) was designed as a low power alternative to classic Bluetooth. However, the use of BLE in dense, Internet of Things (IoT) deployments results in high collision rates and wasted energy. In response, we present an in-depth ...
Connected placement of disaster shelters in modern cities
This paper is motivated by the fact that modern cities are surprisingly vulnerable to large-scale emergencies, such as the recent terrorist attacks on Paris that resulted in the death of 130 people. Disaster shelters are one of the most effective ...
Towards even coverage monitoring with opportunistic sensor networks
Opportunistic sensor networks typically rely on node mobility to monitor an area by collecting samples at different locations. In this paper we show how the mobility in combination with the periodic sampling of nodes causes large differences in the ...
Index Terms
Proceedings of the Eleventh ACM Workshop on Challenged Networks
Recommendations
Acceptance Rates
| Year | Submitted | Accepted | Rate |
|---|---|---|---|
| CHANTS '18 | 27 | 9 | 33% |
| CHANTS '17 | 16 | 6 | 38% |
| CHANTS '16 | 27 | 14 | 52% |
| CHANTS '15 | 27 | 7 | 26% |
| CHANTS '14 | 37 | 15 | 41% |
| CHANTS '13 | 25 | 10 | 40% |
| Overall | 159 | 61 | 38% |



