Abstract: We demonstrate a 40 Gb/s self-synchronizing, all-optical packet
clock recovery circuit designed for efficient packet-mode traffic. The circuit
locks instantaneously and enables sub-nanosecond packet spacing due to the
low clock persistence time. A low-Q Fabry-Perot filter is used as a passive
resonator tuned to the line-rate that generates a retimed clock-resembling
signal. As a reshaping element, an optical power-limiting gate is
incorporated to perform bitwise pulse equalization. Using two preamble
bits, the clock is captured instantly and persists for the duration of the data
packet increased by 16 bits. The performance of the circuit suggests its
suitability for future all-optical packet-switched networks with reduced
transmission overhead and fine network granularity.

Abstract: We here present the Forward Planning Situated Protocol (FPSP), for scalable, energy efficient and fault tolerant data propagation in situated wireless sensor networks. To deal with the increased complexity of such deeply networked sensor systems, instead of emphasizing on a particular aspect of the services provided, i.e. either for low-energy periodic, or low-latency event-driven, or high-success query-based sensing, FPSP uses two novel mechanisms that allow the network operator to adjust the performance of the protocol in terms of energy, latency and success rate on a per-task basis. We emphasize on distributedness, direct or indirect interactions among relatively simple agents, flexibility and robustness.
The protocol operates by employing a series of plan & forward phases through which devices self-organize into forwarding groups that propagate data over discovered paths. FPSP performs a limited number of long range, high power data transmissions to collect information regarding the neighboring devices. The acquired information, allows to plan a (parameterizable long by {\"e}) sequence of short range, lowpower transmissions between nearby particles, based on certain optimization criteria. All particles that decide to respond (based on local criteria) to these long range transmissions enter the forwarding phase during which information is propagated via the acquired plan. Clearly, the duration of the forwarding phases is characterized by the parameter {\"e}, the transmission medium and the processing speed of the devices. In fact the parameter {\"e} provides a mechanism to adjust the protocol performance in terms of the latency--energy trade-off. By reducing {\"e} the latency is reduced at the cost of spending extra energy, while by increasing {\"e}, the energy dissipation is reduced but the latency is increased.
To control the success rate--energy trade-off, particles react locally on environment and context changes by using a set of rules that are based on response thresholds that relate individual-level plasticity with network-level resiliency, motivated by the nature-inspired method for dividing labor, a metaphor of social insect behavior for solving problems [1]. Each particle has an individual response threshold {\`E} that is related to the "local" density (as observed by the particle, [2]); particles engage in propagation of events when the level of the task-associated stimuli exceeds their thresholds. Let s be the intensity of a stimulus associated with a particular sensing task, set by the human authorities. We adopt the response function T_{{\`e}}(s) = s^{n}over s^{n} + {\`e}^{n}, the probability of performing the task as a function of s, where n > 1 determines the steepness of the threshold. Thus, when {\`e} is small (i.e. the network is sparse) then the response probability increases; when s increases (i.e. for critical sensing tasks) the response probability increases as well.
This role-based approach where a selective number of devices do the high cost planning and the rest of the network operates in a low cost state leads to systems that have increased energy efficiency and high fault-tolerance since these long range planning phases allow to bypass obstacles (where no sensors are available) or faulty sensors (that have been disabled due to power failure or other natural events).

Abstract: We propose a MAC protocol for mobile ad hoc networks that
uses power control for the RTS/CTS and DATA frame
transmissions in order to improve energy and capacity
utilization efficiency. Unlike IEEE 802.11, in our scheme the
RTS frames are not sent using the maximum transmission
power to silence neighbouring nodes, and the CTS frames do
not silence all receiving nodes to the same degree. In contrast,
the transmission power of the RTS frames follows a slow
start principle, while the CTS frames, which are sent at
maximum transmission power, prevent the neighbouring
nodes from transmitting their DATA frames with power more
than a computed threshold, while allowing them to transmit at
power levels less than that threshold. This is done by
including in the RTS and the CTS frames additional
information, such as the power of the transmissions, and the
interference tolerance of the nodes. Moreover the DATA
frames are sent at the minimum required transmission power
increased by a small margin to ensure connectivity with the
intended receiver, so as to cause minimal interference to
neighbouring nodes and allow for future interference to be
added to the receiver of the DATA frames. The power to be
used by the transmitter is computed by the recipient of the
RTS frame and is included in the CTS frame. It is expected
that a network with such a power management scheme would
achieve a better throughput performance and more power
savings than a network without such a scheme.

Abstract: We propose a MAC protocol for mobile ad hoc networks that
uses power control for the RTS/CTS and DATA frame
transmissions in order to improve energy and capacity
utilization efficiency. Unlike IEEE 802.11, in our scheme the
RTS frames are not sent using the maximum transmission
power to silence neighbouring nodes, and the CTS frames do
not silence all receiving nodes to the same degree. In contrast,
the transmission power of the RTS frames follows a slow
start principle, while the CTS frames, which are sent at
maximum transmission power, prevent the neighbouring
nodes from transmitting their DATA frames with power more
than a computed threshold, while allowing them to transmit at
power levels less than that threshold. This is done by
including in the RTS and the CTS frames additional
information, such as the power of the transmissions, and the
interference tolerance of the nodes. Moreover the DATA
frames are sent at the minimum required transmission power
increased by a small margin to ensure connectivity with the
intended receiver, so as to cause minimal interference to
neighbouring nodes and allow for future interference to be
added to the receiver of the DATA frames. The power to be
used by the transmitter is computed by the recipient of the
RTS frame and is included in the CTS frame. It is expected
that a network with such a power management scheme would
achieve a better throughput performance and more power
savings than a network without such a scheme.

Abstract: We introduce a new modelling assumption for wireless sensor networks, that of node redeployment (addition of sensor devices during protocol evolution) and we extend the modelling assumption of heterogeneity (having sensor devices of various types). These two features further increase the highly dynamic nature of such networks and adaptation becomes a powerful technique for protocol design. Under these modelling assumptions, we design, implement and evaluate a new power conservation scheme for efficient data propagation. Our scheme is adaptive: it locally monitors the network conditions (density, energy) and accordingly adjusts the sleep-awake schedules of the nodes towards improved operation choices. The scheme is simple, distributed and does not require exchange of control messages between nodes.
Implementing our protocol in software we combine it with two well-known data propagation protocols and evaluate the achieved performance through a detailed simulation study using our extended version of the network simulator ns-2. We focus on highly dynamic scenarios with respect to network density, traffic conditions and sensor node resources. We propose a new general and parameterized metric capturing the trade-offs between delivery rate, energy efficiency and latency. The simulation findings demonstrate significant gains (such as more than doubling the success rate of the well-known Directed Diffusion propagation protocol) and good trade-offs achieved. Furthermore, the redeployment of additional sensors during network evolution and/or the heterogeneous deployment of sensors, drastically improve (when compared to ``equal total power" simultaneous deployment of identical sensors at the start) the protocol performance (i.e. the success rate increases up to four times} while reducing energy dissipation and, interestingly, keeping latency low).

Abstract: We introduce a new modelling assumption in wireless sensor networks, that of node redeployment (addition of sensor devices during the protocol evolution) and we extend the modelling assumption of heterogeneity (having sensor devices of various types). These two features further increase the highly dynamic nature of such networks and adaptation becomes a powerful technique for protocol design. Under this model, we design, implement and evaluate a power conservation scheme for efficient data propagation. Our protocol is adaptive: it locally monitors the network conditions (density, energy) and accordingly adjusts the sleep-awake schedules of the nodes towards best operation choices. Our protocol operates does not require exchange of control messages between nodes to coordinate.Implementing our protocol we combine it with two well-known data propagation protocols and evaluate the achieved performance through a detailed simulation study using our extended version of Ns2. We focus in highly dynamic scenarios with respect to network density, traffic conditions and sensor node resources. We propose a new general and parameterized metric capturing the trade-off between delivery rate, energy efficiency and latency. The simulation findings demonstrate significant gains (such as more than doubling the success rate of the well-known Directed Diffusion propagation paradigm) and good trade-offs. Furthermore, redeployment of sensors during network evolution and/or heterogeneous deployment of sensors drastically improve (when compared to equal total "power" simultaneous deployment of identical sensors at the start) the protocol performance (the success rate increases up to four times while reducing energy dissipation and, interestingly, keeping latency low).

Abstract: This chapter aims at presenting certain important aspects of the design of lightweight, event-driven algorithmic solutions for data dissemination in wireless sensor networks that provide support for reliable, efficient and concurrency-intensive operation. We wish to emphasize that efficient solutions at several levels are needed, e.g.~higher level energy efficient routing protools and lower level power management schemes. Furthermore, it is important to combine such different level methods into integrated protocols and approaches. Such solutions must be simple, distributed and local. Two useful algorithmic design principles are randomization (to trade-off efficiency and fault-tolerance) and adaptation (to adjust to high network dynamics towards improved operation). In particular, we provide a) a brief description of the technical specifications of state-of-the-art sensor devices b) a discussion of possible models used to abstract such networks, emphasizing heterogeneity, c) some representative power management schemes, and d) a presentation of some characteristic protocols for data propagation. Crucial efficiency properties of these schemes and protocols (and their combinations, in some cases) are investigated by both rigorous analysis and performance evaluations through large scale simulations.

Abstract: Here we survey various computational models for Wireless Sensor Networks (WSNs). The population protocol model (PP) considers networks of tiny mobile finite-state artifacts that can sense the environment and communicate in pairs to perform a computation. The mediated population protocol model (MPP) enhances the previous model by allowing the communication links to have a constant size buffer, providing more computational power. The graph decision MPP model (GDM) is a special case of MPP that focuses on the MPP's ability to decide graph properties of the network. Another direction towards enhancing the PP is followed by the PALOMA model in which the artifacts are no longer finite-state automata but Turing Machines of logarithmic memory in the population size. A different approach to modeling WSNs is the static synchronous sensor field model (SSSF) which describes devices communicating through a fixed communication graph and interacting with their environment via input and output data streams. In this survey, we present the computational capabilities of each model and provide directions for further research.

Abstract: Andrews et al. [Automatic method for hiding latency in high bandwidth networks, in: Proceedings of the ACM Symposium on Theory of Computing, 1996, pp. 257–265; Improved methods for hiding latency in high bandwidth networks, in: Proceedings of the Eighth Annual ACM Symposium on Parallel Algorithms and Architectures, 1996, pp. 52–61] introduced a number of techniques for automatically hiding latency when performing simulations of networks with unit delay links on networks with arbitrary unequal delay links. In their work, they assume that processors of the host network are identical in computational power to those of the guest network being simulated. They further assume that the links of the host are able to pipeline messages, i.e., they are able to deliver P packets in time O(P+d) where d is the delay on the link.
In this paper we examine the effect of eliminating one or both of these assumptions. In particular, we provide an efficient simulation of a linear array of homogeneous processors connected by unit-delay links on a linear array of heterogeneous processors connected by links with arbitrary delay. We show that the slowdown achieved by our simulation is optimal. We then consider the case of simulating cliques by cliques; i.e., a clique of heterogeneous processors with arbitrary delay links is used to simulate a clique of homogeneous processors with unit delay links. We reduce the slowdown from the obvious bound of the maximum delay link to the average of the link delays. In the case of the linear array we consider both links with and without pipelining. For the clique simulation the links are not assumed to support pipelining.
The main motivation of our results (as was the case with Andrews et al.) is to mitigate the degradation of performance when executing parallel programs designed for different architectures on a network of workstations (NOW). In such a setting it is unlikely that the links provided by the NOW will support pipelining and it is quite probable the processors will be heterogeneous. Combining our result on clique simulation with well-known techniques for simulating shared memory PRAMs on distributed memory machines provides an effective automatic compilation of a PRAM algorithm on a NOW.

Abstract: We call radiation at a point of a wireless network the total amount of electromagnetic quantity (energy or power density) the point is exposed to. The impact of radiation can be high and we believe it is worth studying and control; towards radiation aware wireless networking we take (for the first time in the study of this aspect) a distributed computing, algorithmic approach. We exemplify this line of research by focusing on sensor networks, studying the minimum radiation path problem of finding the lowest radiation trajectory of a person moving from a source to a destination point in the network region. For this problem, we sketch the main ideas behind a linear program that can provide a tight approximation of the optimal solution, and then we discuss three heuristics that can lead to low radiation paths. We also plan to investigate the impact of diverse node mobility to the heuristics' performance.

Abstract: We study the important problem of tracking moving
targets in wireless sensor networks. We try to overcome the
limitations of standard state of the art tracking methods based on
continuous location tracking, i.e. the high energy dissipation and
communication overhead imposed by the active participation of
sensors in the tracking process and the low scalability, especially
in sparse networks. Instead, our approach uses sensors in a
passive way: they only record and judiciously spread information
about observed target presence in their vicinity; this information
is then used by the (powerful) tracking agent to locate the target
by just following the traces left at sensors. Our protocol is greedy,
local, distributed, energy efﬁcient and very successful, in the
sense that (as shown by extensive simulations) the tracking agent
manages to quickly locate and follow the target; also, we achieve
good trade-offs between the energy dissipation and latency.

Abstract: Modern Wireless Sensor Networks offer an easy, lowcost
and reliable alternative to the back-end for monitoring
and controlling large geographical areas like Buildings
and Industries. We present the design and implementation details of an open and efficient Prototype System as a solution for low-cost BMS that comprises of heterogeneous, small-factor wireless devices. Placing that in the context of Internet of Things we come up with a solution that can cooperate with other systems installed on the same site to lower power consumption and costs as well as benefit humans that use its services in an transparent way. We evaluate and assess key aspects of the performance of our prototype. Our findings indicate specific approaches
to reduce the operation costs and allow the development of open applications.

Abstract: In this work we study energy efficient routing strategies
for wireless ad-hoc networks. In this kind of networks,
energy is a scarce resource and its conservation
and efficient use is a major issue. Our strategy follows
the multi-cost routing approach, according to which a
cost vector of various parameters is assigned to each
link. The parameters of interest are the number of hops
on a path, and the residual energy and the transmission
power of the nodes on the path. These parameters
are combined in various optimization functions,
corresponding to different routing algorithms, for selecting
the optimal path. We evaluate the routing algorithms
proposed in a number of scenarios, with respect
to energy consumption, throughput and other performance
parameters of interest. From the experiments
conducted we conclude that routing algorithms that take
into account energy related parameters, increase the
lifetime of the network, while achieving better performance
than other approaches, such as minimum hop
routing.

Abstract: The technological as well as software advances in
microelectronics and embedded component design have led to the
development of low cost, small-sized devices capable of forming
wireless, ad-hoc networks and sensing a number of qualities of
their environment, while performing computations that depend
on the sensed qualities as well as information received by their
peers. These sensor networks rely on the collective power of
the separate devices as well as their computational and sensing
capabilities to understand "global" environmental states through
locally sampled information and local sensor interactions. Due
to the locality of the sensor networks, that naturally arises due
to the locality of their communications capabilities, a number
of interesting connections exist between these networks and
geometrical concepts and problems. In this paper we study two
simple problems that pertain to the formation of lowpower
and low interference communication patterns in fixed topology
sensor networks. We study the problem of using multihop
communication links instead of direct ones as well as the problem
of forming a communication ring of sensor networks so as to
reduce power consumption as well as interference from other
nodes. Our focus is on the connection between sensor networks
and geometrical concepts, rather than on practicality, so as to
highlight their interrelationship.

Abstract: We extend here the Population Protocol model of Angluin et al. [2004,2006] in order to model more powerful networks of resource-limited agents that are possibly mobile. The main feature of our extended model, called the Mediated Population Protocol (MPP) model, is to allow edges of the communication graph to have states that belong to a constant size set. We then allow the protocol rules for pairwise interactions to modify the corresponding edge state. Protocol specifications preserve both uniformity and anonymity. We first focus on the computational power of the MPP model on complete communication graphs and initially identical edges. We provide the following exact characterization for the class MPS of stably computable predicates: A predicate is in MPS iff it is symmetric and is in NSPACE(n^2)$. We finally ignore the input to the agents and study MPP's ability to compute graph properties.

Abstract: We extend here the Population Protocol model of Angluin et al. [2004] in order to model more powerful networks of very small resource-limited artefacts (agents) that are possibly mobile. Communication can happen only between pairs of artefacts. A communication graph (or digraph) denotes the permissible pairwise interactions. The main feature of our extended model is to allow edges of the communication graph, G, to have states that belong to a constant size set. We also allow edges to have readable only costs, whose values also belong to a constant size set. We then allow the protocol rules for pairwise interactions to modify the corresponding edge state. Thus, our protocol specifications are still independent of the population size and do not use agent ids, i.e. they preserve scalability, uniformity and anonymity. Our Mediated Population Protocols (MPP) can stably compute graph properties of the communication graph. We show this for the properties of maximal matchings (in undirected communication graphs), also for finding the transitive closure of directed graphs and for finding all edges of small cost. We demonstrate that our mediated protocols are stronger than the classical population protocols, by presenting a mediated protocol that stably computes the product of two positive integers, when G is the complete graph. This is not a semilinear predicate. To show this fact, we state and prove a general Theorem about the Composition of two stably computing mediated population protocols. We also show that all predicates stably computable in our model are (non-uniformly) in the class NSPACE(m), where m is the number of edges of the communication graph. We also define Randomized MPP and show that, any Peano predicate accepted by a MPP, can be verified in deterministic Polynomial Time.

Abstract: Recent rapid developments in micro-electro-mechanical systems
(MEMS), wireless communications and digital electronics have already
led to the development of tiny, low-power, low-cost sensor devices.
Such devices integrate sensing, limited data processing and restricted
communication capabilities.
Each sensor device individually might have small utility, however the
effective distributed co-ordination of large numbers of such devices can
lead to the efficient accomplishment of large sensing tasks. Large numbers
of sensors can be deployed in areas of interest (such as inaccessible
terrains or disaster places) and use self-organization and collaborative
methods to form an ad-hoc network.
We note however that the efficient and robust realization of such large,
highly-dynamic, complex, non-conventional networking environments is
a challenging technological and algorithmic task, because of the unique
characteristics and severe limitations of these devices.
This talk will present and discuss several important aspects of the
design, deployment and operation of sensor networks. In particular, we
provide a brief description of the technical specifications of state-of-theart
sensor, a discussion of possible models used to abstract such networks,
a discussion of some key algorithmic design techniques (like randomization,
adaptation and hybrid schemes), a presentation of representative
protocols for sensor networks, for important problems including data
propagation, collision avoidance and energy balance and an evaluation
of crucial performance properties (correctness, efficiency, fault-tolerance)
of these protocols, both with analytic and simulation means.

Abstract: In this work we extend the population protocol model of Angluin et al., in
order to model more powerful networks of very small resource limited
artefacts (agents) that is possible to follow some unpredictable passive
movement. These agents communicate in pairs according to the commands of
an adversary scheduler. A directed (or undirected) communication graph
encodes the following information: each edge (u,\~{o}) denotes that during the
computation it is possible for an interaction between u and \~{o} to happen in
which u is the initiator and \~{o} the responder. The new characteristic of
the proposed mediated population protocol model is the existance of a
passive communication provider that we call mediator. The mediator is a
simple database with communication capabilities. Its main purpose is to
maintain the permissible interactions in communication classes, whose
number is constant and independent of the population size. For this reason
we assume that each agent has a unique identifier for whose existence the
agent itself is not informed and thus cannot store it in its working
memory. When two agents are about to interact they send their ids to the
mediator. The mediator searches for that ordered pair in its database and
if it exists in some communication class it sends back to the agents the
state corresponding to that class. If this interaction is not permitted to
the agents, or, in other words, if this specific pair does not exist in
the database, the agents are informed to abord the interaction. Note that
in this manner for the first time we obtain some control on the safety of
the network and moreover the mediator provides us at any time with the
network topology. Equivalently, we can model the mediator by communication
links that are capable of keeping states from a edge state set of constant
cardinality. This alternative way of thinking of the new model has many
advantages concerning the formal modeling and the design of protocols,
since it enables us to abstract away the implementation details of the
mediator. Moreover, we extend further the new model by allowing the edges
to keep readable only costs, whose values also belong to a constant size
set. We then allow the protocol rules for pairwise interactions to modify
the corresponding edge state by also taking into account the costs. Thus,
our protocol descriptions are still independent of the population size and
do not use agent ids, i.e. they preserve scalability, uniformity and
anonymity. The proposed Mediated Population Protocols (MPP) can stably
compute graph properties of the communication graph. We show this for the
properties of maximal matchings (in undirected communication graphs), also
for finding the transitive closure of directed graphs and for finding all
edges of small cost. We demonstrate that our mediated protocols are
stronger than the classical population protocols. First of all we notice
an obvious fact: the classical model is a special case of the new model,
that is, the new model can compute at least the same things with the
classical one. We then present a mediated protocol that stably computes
the product of two nonnegative integers in the case where G is complete
directed and connected. Such kind of predicates are not semilinear and it
has been proven that classical population protocols in complete graphs can
compute precisely the semilinear predicates, thus in this manner we show
that there is at least one predicate that our model computes and which the
classical model cannot compute. To show this fact, we state and prove a
general Theorem about the composition of two mediated population
protocols, where the first one has stabilizing inputs. We also show that
all predicates stably computable in our model are (non-uniformly) in the
class NSPACE(m), where m is the number of edges of the communication
graph. Finally, we define Randomized MPP and show that, any Peano
predicate accepted by a Randomized MPP, can be verified in deterministic
polynomial time.

Abstract: This is a joint work with Ioannis Chatzigiannakis and Othon Michail.
We discuss here the population protocol model and most of its well-known extensions. The population protocol model aims to represent sensor networks consisting of tiny computational devices with sensing capabilities that follow some unpredictable and uncontrollable mobility pattern. It adopts a minimalistic approach and, thus, naturally computes a quite restricted class of predicates and exhibits almost no fault-tolerance. Most recent approaches make extra realistic and implementable assumptions, in order to gain more computational power and/or speed-up the time to convergence and/or improve fault-tolerance. In particular, the mediated population protocol model, the community protocol model, and the PALOMA model, which are all extensions of the population protocol model, are thoroughly discussed. Finally, the inherent difficulty of verifying the correctness of population protocols that run on complete communication graphs is revealed, but a promising algorithmic solution is presented.

Abstract: In emerging pervasive scenarios, data is collected by sensing devices in streams that occur at several distributed points of observation. The size of the data typically far exceeds the storage and computational capabilities of the tiny devices that have to collect and process them. A general and challenging task is to allow (some of) the nodes of a pervasive network to collectively perform monitoring of a neighbourhood of interest by issuing continuous aggregate queries on the streams observed in its vicinity. This class of algorithms is fully decentralized and diffusive in nature: collecting all the data at a few central nodes of the network is unfeasible in networks of low capability devices or in the presence of massive data sets. Two main problems arise in this scenario: (i) the intrinsic complexity of maintaining statistics over a data stream whose size greatly exceeds the capabilities of the device that performs the computation; (ii) composing the partial outcomes computed at different points of observation into an accurate, global statistic over a neighbourhood of interest, which entails coping with several problems, last but not least the receipt of duplicate information along multiple paths of diffusion.
Streaming techniques have emerged as powerful tools to achieve the general goals described above, in the first place because they assume a computational model in which computational and storage resources are assumed to be far exceeded by the amount of data on which computation occurs. In this contribution, we review the main streaming techniques and provide a classification of the computational problems and the applications they effectively address, with an emphasis on decentralized scenarios, which are of particular interest in pervasive networks

Abstract: We explore the capability of a network of extremely limited computational entities to decide properties about itself or any of its subnetworks. We consider that the underlying network of the interacting entities (devices, agents, processes etc.) is modeled by an interaction graph that reflects the network’s connectivity. We examine the following two cases: First, we consider the case where the input graph is the whole interaction graph and second where it is some subgraph of the interaction graph given by some preprocessing on the network. In each case, we devise simple graph protocols that can decide properties of the input graph. The computational entities, that are called agents, are modeled as finite-state automata and run the same global graph protocol. Each protocol is a fixed size grammar, that is, its description is independent of the size (number of agents) of the network. This size is not known by the agents. We present two simple models (one for each case), the Graph Decision Mediated Population Protocol (GDMPP) and the Mediated Graph Protocol (MGP) models, similar to the Population Protocol model of Angluin et al., where each network link (edge of the interaction graph) is characterized by a state taken from a finite set. This state can be used and updated during each interaction between the corresponding agents. We provide some example protocols and some interesting properties for the two models concerning the computability of graph languages in various settings (disconnected input graphs, stabilizing input graphs). We show that the computational power within the family of all (at least) weakly-connected input graphs is fairly restricted. Finally, we give an exact characterization of the class of graph languages decidable by the MGP model in the case of complete interaction graphs: it is equal to the class of graph languages decidable by a nondeterministic Turing Machine of linear space that receives its input graph by its adjacency matrix representation.

Abstract: We propose and evaluate the performance of a new MAC-layer protocol for mobile ad hoc networks, called the Slow Start Power Controlled (abbreviated SSPC) protocol. SSPC improves on IEEE 802.11 by using power control for the RTS/CTS and DATA frame transmissions, so as to reduce energy consumption and increase network throughput and lifetime. In our scheme the transmission power used for the RTS frames is not constant, but follows a slow start principle. The CTS frames, which are sent at maximum transmission power, prevent the neighbouring nodes from transmitting their DATA frames at power levels higher than a computed threshold, while allowing them to transmit at power levels less than that threshold. Reduced energy consumption is achieved by adjusting the node transmission power to the minimum required value for reliable reception at the receiving node, while increase in network throughput is achieved by allowing more transmissions to take place simultaneously. The slow start principle used for calculating the appropriate DATA frames transmission power and the possibility of more simultaneous collision-free transmissions differentiate the SSPC protocol from the other MAC solutions proposed for IEEE 802.11. Simulation results indicate that the SSPC protocol achieves a significant reduction in power consumption, average packet delay and frequency of RTS frame collisions, and a significant increase in network throughput and received-to-sent packets ratio compared to IEEE 802.11 protocol.