To efficiently use alternate paths during periods of congestion, we have devised prioritized Dynamic Routing
Control Agent (pDRCA) that (1) selects best links to meet the bandwidth and delay requirements of traffic, (2)
provides load-balancing and traffic prioritization when multiple topologies are available, and (3) handles changes
in link quality and traffic demand, and link outages. pDRCA provides multiplatform load balancing to maximize
SATCOM (both P2P and multi-point) and airborne links utilization. It influences link selection by configuring the
cost metrics on a router's interface, which does not require any changes to the routing protocol itself. It supports
service differentiation of multiple traffic priorities by providing more network resources to the highest priority
flows. pDRCA does so by solving an optimization problem to find optimal links weights that increase throughput
and decrease E2E delay; avoid congested, low quality, and long delay links; and exploit path diversity in the network. These optimal link weights are sent to the local agents to be configured on individual routers per traffic priority. The pDRCA optimization algorithm has been proven effective in improving application performance. We created a variety of different test scenarios by varying traffic profile and link behavior (stable links, varying capacity, and link outages). In the scenarios where high priority traffic experienced significant loss without pDRCA, the average loss was reduced from 49.5% to 13% and in some cases dropped to 0%. Currently, pDRCA is integrated with an open-source software router and priority queues on Linux as a component of Open Tactical Router (OTR), which is being developed by ONR DTCN program.
Existing distributed approaches to topology control are poor at exploiting the large configuration space of cognitive
radios and use extensive inter-node synchronization to aim at optimality. We have created a framework to design and
study distributed topology control algorithms that combine network-formation games with machine learning. In our
approach, carefully designed incentive mechanisms drive distributed autonomous agents towards a pre-determined
system-wide optimum. The algorithms rely on game players to pursue selfish actions through low-complexity greedy
algorithms with low or no signaling overhead. Convergence and stability are ensured through proper mechanism design
that eliminates infinite adaptation process. The framework also includes game-theoretic extensions to influence behavior
such as fragment merging and preferring links to weakly connected neighbors. Learning allows adaptations that prevent
node starvation, reduce link flapping, and minimize routing disruptions by incorporating network layer feedback in
cost/utility tradeoffs. The algorithms are implemented in Telcordia Wireless IP Scalable Network Emulator. Using
greedy utility maximization as a benchmark, we show improvements of 13-40% for metrics such as the numbers of
disconnected fragments and weakly connected nodes, topology stability, and disruption to user flows. The proposed
framework is particularly suitable to cognitive radio networks because it can be extended to handle heterogeneous users
with different utility functions and conflicting objectives. Desired outcome is then achieved by application of standard
cooperation techniques such as utility transfer (payments). Additional cross-layer optimizations are possible by playing
games at multiple layers in a highly scalable manner.
KEYWORDS: Human-machine interfaces, Commercial off the shelf technology, Sensor networks, Receivers, Network architectures, Sensors, Switches, Local area networks, Satellites, Systems modeling
WISER is a scalable network emulation tool for networks with several hundred heterogeneous wireless nodes. It
provides high-fidelity network modeling, exchanges packets in real-time, and faithfully captures the complex
interactions among network entities. WISER runs on inexpensive COTS platforms and represents multiple full network
stacks, one for each individual virtual node. It supports a flexible open source router platform (XORP) to implement
routing protocol stacks. WISER offers wireless MAC emulation capabilities for different types of links, waveforms,
radio devices, etc. We present experiments to demonstrate WISER's capabilities enabling a new paradigm for
performance evaluation of mobile sensor and ad-hoc networks.
The communication of Future Combat Systems (FCS), with rigid timing and reliability requirements, has posed
a great challenge for the existing popular transport layer protocols such as TCP and UDP. The Stream Control
Transmission Protocol (SCTP), first designed to transmit telephony signaling messages over Internet, is a promising
transport layer candidate for FCS networks. The new SCTP features such as multi-homing, multi-streaming,
and enhanced security can significantly improve the performance of FCS applications. In this paper, we propose
modifications to the congestion control and multi-streaming parts of current SCTP specifications to allow the
support of QoS for FCS applications. Multiple streams in an SCTP association provide an aggregation mechanism
to accommodate heterogeneous objects, which belong to the same application but may require different
types of QoS from the network. However, the current SCTP specification lacks an internal mechanism to support
the preferential treatment among its streams. Our work introduces the concept of grouping SCTP streams into
subflows based on their required QoS. We propose to modify the current SCTP to implement subflows (named
SF-SCTP), each with its own flow and congestion mechanism to prevent the so-called false sharing problem.
To improve the fairness of SF-SCTP towards the original SCTP, we integrate Fractional Congestion Control
into the design. The throughput performance evaluation of SF-SCTP is studied through ns-2 experiments in a
simplified Diff-Serv network. The simulation results prove the SF-SCTP's capability to support QoS among its
streams, confirm the accuracy of the analytic models, and justify our effects to integrate FCC into SF-SCTP
since it improves the fairness between SF-SCTP and the original SCTP.
This paper presents an improvement of a novel analytic model for
ad hoc networks based on Markov chains whose states represent node
degree and the number of link failures. The model divides a
geographic area into logical hexagonal cells, where random walk
with probabilistic state-transition matrix determines link
creation/failure. We can thus compute two important metrics
characterizing the dynamics of a node's random movement: the
expected times for the number of link changes to drop below and
for the node degree to exceed a threshold. We obtained the
two-dimensional Markov chain that allows us to apply these two
metrics as the selection rules for the virtual backbone formation
algorithm. Hence, our model is used to analyze the performance of
service discovery architectures based on virtual backbone in
mobile ad-hoc networks. We also plan to extend the created
modeling framework to derive a number of additional metrics that
characterize network connectivity, capacity, and survivability.
Because the model is capable of computing the dynamics and the
expected value of the number of a node's neighbors, it can also be
used to estimate the level of interference as well as achievable
and sustainable routing path diversity, degree of network
connectivity, and the stability of routing tables. We expect to
apply our modeling framework to analytic assessment of the
stability of routing domains. The rate and expected values at
which the nodes move in and out of domains characterize the rate
of degradation of optimally built routing domains, and hence the
resulting routing scalability and overhead.
The Stream Control Transmission Protocol (SCTP), a general-purpose
transport layer protocol standardized by the IETF, has been a promising
candidate to join UDP and TCP as a core protocol. The new SCTP features
such as multi-homing, multi-streaming, and enhanced security can
significantly improve the performance of FCS applications.
Multi-streaming provides an aggregation mechanism in an SCTP association
to accommodate heterogeneous objects, which belong to the same
application but may require different type of QoS from the network.
However, the current SCTP specification lacks an internal mechanism to
support the preferential treatment among its streams. We introduce the
concept of subflow and propose to modify the current SCTP such that the
streams are grouped into several subflows according to their required
QoS. It is also proposed that each subflow should implement its own
congestion control to prevent the so-called false sharing. To
compare the throughput differences, analytic models have been derived
for the current SCTP and for the subflow-capable SCTP with different
congestion control mechanisms. Simulations with ns-2 have been used to
qualitatively demonstrate the throughput differences of these
designs in a simplified diff-serv network. The analytical models are
confirmed to accurately reflect the SCTP behavior. The simulation also
shows that our proposed solution is able to efficiently support QoS
among the SCTP streams.
We present Dynamic Survivable Resource Pooling (DSRP) that provides
survivable access to resources and services in battlefield networks. The
servers accessed by mobile users (e.g., FCS backbone managers, TPKI,
Bandwidth Brokers, Situation Awareness/Common Network Picture, SIP) are pooled together for higher availability and failover; the Name
Servers (NSs) are responsible for maintaining server pools, load balancing, and server discovery. In the DSRP scheme, NSs are placed on a virtual
backbone (VB): a highly distributed, scalable, and survivable network
formed and maintained through one-hop beacons. By making locally scoped
decisions, VB is capable of reorganizing both itself and pool registrations
in response to mobility, failures, and partitioning. A proof-of-concept of
the DSRP successfully demonstrated its survivability.
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